In 2025, many JMAI authors make outstanding contributions to our journal. Their articles published with us have received very well feedback in the field and stimulate a lot of discussions and new insights among the peers.
Hereby, we would like to highlight some of our outstanding authors who have been making immense efforts in their research fields, with a brief interview of their unique perspective and insightful view as authors.
Outstanding Authors (2025)
Qianhui Lu, Abbott Laboratories, USA
Charbel Alhelou, ArcaScience, France
Dharambir Mahto, Sriya.AI, USA
Hannah Ong, The Ohio State University, USA
Pedro Angelo Basei de Paula, Federal University of Paraná, Brazil
Wahid Ullah, Riphah International University, Pakistan
Nino Gvajaia, Tbilisi State Medical University, USA
Mohammad Najeh Samara, Binghamton University, USA
Anupama Nair, Virginia Commonwealth University, USA
Afiq Izzudin A. Rahim, Universiti Sains Malaysia, Malaysia
Elad Shvartz, The Kaplan Medical Center, Israel
Hang Dao Viet, Hanoi Medical University Hospital, Vietnam
Iliyas Ibrahim Iliyas, Abubakar Tafawa Balewa University, Nigeria
Matthew Kaufman, Stanford University, USA
Sasanka Katreddi, Daimler Truck North America, USA
Yong Bae Kim, Korea Association of Health Promotion, Korea
Vinicius Anjos de Almeida, The University of São Paulo, Brazil
Srinivasa Ramanujan Boora, Penn State Health Holy Spirit Medical Center, USA
Ashkan Fakharifar, Islamic Azad University, Iran
Outstanding Author
Qianhui Lu
Qianhui Lu is a Staff AI Engineer with Abbott Laboratories spearheading Data and Innovation mission critical projects. Her curiosity and passion for AI sparked during her undergraduate years when she met a PhD candidate specializing in data mining and machine learning. Since then, she has sharpened her expertise in AI and machine learning through roles as a Machine Learning Engineer, AI Fellow, Data Scientist, and AI Engineer. She earned a bachelor's degree in engineering from Penn State University, followed by a master's in Innovation Management from Brown University, where she worked on computer vision algorithms for Augmented and Virtual Reality. She also holds a master's in Data Analytics from San Jose State University, where she honed her natural language processing (NLP) skills. Her career includes research in multi-modal semantics extraction and developing NLP tools for the legal industry. At Abbott, she harnesses cutting-edge technologies such as machine learning and AI to enhance health care solutions. She is dedicated to integrating AI technologies into tools and solutions that make a positive impact on people's lives.
JMAI: What do you regard as a good academic paper?
Qianhui: A stellar academic paper in the dynamic field of Artificial Intelligence (AI) and health care addresses significant and relevant issues, resonating with current challenges or advancements. It introduces fresh, innovative ideas or solutions, contributing new knowledge that pushes the boundaries of what's known. In my opinion, data and evidence are the backbone of any good paper. They should be robust, reliable, and convincingly support the results. The analysis should be thorough, with interpretations and conclusions that logically follow from the data presented. The potential impact or real-world application of the paper is another key factor. A great paper has the power to influence future research, policy, or practice, making a real difference in the field. In addition, the methodology must be rock-solid, clearly described, and well-justified, ensuring credibility and replicability. A comprehensive literature review situates the research within the broader context, highlighting unique contributions. Accurate and up-to-date references and citations are essential, showing the paper's foundation in established research. Clarity and organization are crucial as well, ensuring that the paper is a pleasure to read with a logical flow. In essence, a good academic paper blends robust data, significant impact, relevance, originality, clarity, solid methodology, thorough analysis, comprehensive literature review, and ethical integrity.
JMAI: What are the most commonly encountered difficulties in academic writing?
Qianhui: One of the biggest hurdles in academic writing is making complex ideas clear and engaging—like turning an outstanding LLM or complicated medical diagnostic algorithm into a user-friendly app. Balancing originality with thorough research is another tricky task—think of it as adding your unique AI implementation or medical breakthrough to a well-established protocol or heavily regulated space. Time management can also be a challenge as authors are usually juggling multiple projects, with research, writing, and revisions. Furthermore, handling feedback can be tough, but it's like fine-tuning a machine learning model or refining a treatment plan—sometimes it takes quite a bit of tweaking to get it just right. Despite these challenges, the process is incredibly rewarding.
JMAI: What is fascinating about academic writing?
Qianhui: Academic writing is like embarking on a thrilling adventure where one gets to be both a detective and an innovator. Academic writing allows us to dive deep into the unknown, explore uncharted territories, and contribute to the ever-evolving landscape of AI and health care. It's a platform where creativity meets rigor, where new hypothesis is tested and every result analyzed brings us closer to solving real-world problems. Plus, there's the thrill of seeing our work inspire others, spark new ideas, and drive future research. In essence, academic writing is a blend of passion, curiosity, and dedication. It's about pushing the boundaries of what's possible and making a tangible impact on the world.
(by Brad Li, Masaki Lo)
Charbel Alhelou
Charbel Alhelou is a Doctor of Pharmacy with master’s degrees in Clinical and Preclinical Pharmacology, Research in Pharmacoepidemiology, and Business Administration. He has contributed to various research projects, including a study on the impact of SGLT2 inhibitors on atrial fibrillation. With four years of experience in community pharmacy, he has developed a deep understanding of patient needs, effective communication, and the value of diverse perspectives in healthcare. Currently, as a Product Manager at ArcaScience, he focuses on leveraging AI to tackle key challenges in the pharmaceutical industry. He has contributed to various AI-driven healthcare projects, including the detection and classification of clinical endpoints, the development of a chatbot for hidradenitis suppurativa patients, a model for the detection of the publications type, and the creation of a drug-drug interaction (DDI) detection algorithm. Over the past 18 months, he has led the Benefit-Risk Assessment Project, integrating advanced technologies and prioritizing patient-centric approaches to enhance drug development.
From Alhelou’s perspectives, academic writing serves as a means of transmitting knowledge, while scientific writing provides a platform for sharing discoveries. To him, a researcher’s findings must be clearly understandable and well-documented to be considered valid evidence. Transmitting and publishing evidence is crucial in healthcare, as it leads to better evidence-based decision-making, ultimately improving patient health. In the field of AI, scientific writing is still in its early stages, making it essential to share even small improvements and findings. He believes this collaborative approach helps researchers and practitioners maximize the potential of AI while addressing ethical considerations and optimizing time management.
Dr. Alhelou reckons that transparency is crucial in academic writing—not just for conveying results, but also for clearly outlining the conditions under which those results were obtained. One of the main challenges in both science and AI is generalization. In his view, the more data are contextualized, the more researchers advance science without introducing bias.
Lastly, Dr. Alhelou emphasizes that science now needs a more comprehensive approach—one that includes all perspectives, failures, and every piece of information, no matter how small. This broader transparency is essential for making scientific research more effective in improving human lives.
(by Sasa Zhu, Brad Li)
Dharambir Mahto
Dharambir Mahto is a dedicated researcher specializing in artificial intelligence and machine learning applications. His primary research focuses on the comparative study of AI2-SXI versus traditional ML/DL models in predicting patient readmissions, aiming to enhance predictive accuracy and improve patient outcomes. With a strong background in data science and healthcare analytics, his recent work—conducted in collaboration with Sriya.AI—investigates the efficiency, interpretability, and scalability of AI2-SXI compared to conventional models. He is passionate about bridging the gap between advanced AI techniques and practical clinical applications, optimizing healthcare predictions, reducing hospital readmissions, and supporting evidence-based medical practices. Through his research, he strives to ensure that technology-driven solutions are both effective and ethically sound, further advancing AI’s role in healthcare.
From Dharambir’s perspective, a well-written academic paper includes several key elements. It should start with a clear and concise title that reflects the main focus of the study. The abstract should provide a brief summary of the research, highlighting the objectives, methods, key findings, and conclusions. A strong introduction sets the stage by explaining the research problem, its significance, and the study's objectives. The literature review should provide background information, discussing previous research and how the current study fits into the existing body of knowledge. A well-detailed methodology section ensures transparency by explaining how the research was conducted. The results section presents findings clearly, often supported by tables or figures, while the discussion interprets these results in relation to existing studies. Finally, the conclusion summarizes key takeaways and suggests potential directions for future research. Proper citations and references maintain academic integrity, and clear, concise writing makes the paper engaging and easy to understand.
Dharambir emphasizes that authors must consider several key factors when preparing their writing. First, they should clearly define their research question and ensure their study contributes something valuable to their field. The structure and organization of the paper should follow the guidelines of the target journal, including formatting, referencing style, and word limits. Authors must provide a thorough literature review to establish context and justify their research. The methodology should be detailed and transparent to allow replication. Data analysis must be accurate, and results should be presented clearly with appropriate figures and tables. In the discussion, authors should interpret their findings objectively and acknowledge limitations. Proper citations and references are crucial to avoid plagiarism. Additionally, maintaining clarity and conciseness in writing enhances readability. Before submission, authors should carefully proofread and edit their work, possibly seeking feedback from colleagues or mentors. Finally, they should ensure they comply with ethical standards, including authorship criteria, conflict of interest disclosures, and ethical approval for studies involving human or animal subjects.
“To all academic writers dedicated to advancing scientific progress—your work is invaluable. Every paper you write contributes to the collective knowledge of humanity, driving innovation and shaping the future. The journey of research may be challenging, but your persistence, curiosity, and dedication make a real difference. Keep questioning, keep exploring, and keep sharing your insights with the world. Your efforts inspire others and pave the way for new discoveries. Stay motivated, embrace the process, and never underestimate the impact of your contributions,” says Dharambir.
(by Sasa Zhu, Brad Li)
Hannah Ong
Hannah Ong trains at The Ohio State University College of Medicine and has a specialized interest in artificial intelligence (AI) applications in medicine and interdisciplinary education. Her research focuses on integrating machine learning, leadership development, and hands-on AI training for pre-college students interested in medicine, engineering, and technology. She is the co-founder of the LeadingAI program, a pioneering initiative that trains students in AI and reinforcement learning through AWS DeepRacer, fostering leadership and technical skills. The program has produced multiple globally ranked competitors in AI-driven racing and has been instrumental in developing a structured AI curriculum. She is passionate about bridging AI and medicine, leveraging emerging technologies to enhance education, research, and patient care. She hopes to continue to advocate for the integration of AI education in early academic settings to cultivate the next generation of leaders in technology and healthcare.
According to Hannah, a strong academic paper should include: a clear research objective – define the significance of the study and its impact on the field; comprehensive literature review – contextualize the work by building upon existing research; robust methodology – ensure clarity and reproducibility in research design; data-driven analysis – use well-structured figures, tables, and statistical models to support findings; critical discussion and interpretation – address limitations, future directions, and practical applications; concise and engaging writing – maintain clarity and precision while presenting complex ideas, and ethical research practices – transparency in data handling, authorship, and conflict disclosures is key.
Hannah emphasizes that authors should bear in mind the following elements when they prepare to write. First, target the right audience, tailoring the writing for medical, AI, or interdisciplinary journals accordingly. Seek peer feedback, involving domain experts to enhance rigor and perspective. She adds that authors should ensure reproducibility, accurate citations, and ethical considerations in writing. Well-designed figures and tables can enhance comprehension as well. Furthermore, iterative drafting and peer reviews significantly also improve clarity and impact.
“Academic writing remains one of the most influential ways to advance scientific progress, bridging innovative ideas with practical applications. Whether you are examining the integration of AI in healthcare or exploring leadership in education, your work enriches a growing repository of knowledge that makes a tangible impact.
While the challenges of peer review, funding constraints, and interdisciplinary dialogue can be demanding, they also offer essential opportunities for professional and personal growth. For those working at the intersection of AI and medicine, the potential for breakthroughs—from personalized medicine to improved diagnostic tools—is especially significant. I encourage you to embrace curiosity, actively seek mentorship, and remain dedicated to innovation. Your research is not only advancing your field but also shaping the future of science and technology,” says Hannah.
(by Sasa Zhu, Brad Li)
Pedro Angelo Basei de Paula
Pedro Angelo Basei de Paula is a sixth-year medical student at the Federal University of Paraná (UFPR). He has been contributing to research with AI-powered solutions for the automatic structuring of medical consultations with Voa Health, as well as analyzing datasets with AI in mental health and clinical communication. He is also preparing for a research experience in Canada, where he will contribute to an AI-driven eHealth platform that integrates emotional recognition and behaviour change strategies into medical practice. He is deeply interested in artificial intelligence, psychiatry, healthcare innovation, piano playing, and the profound questions surrounding the Universe and consciousness. With a background in engineering, he is committed to enhancing decision-making, documentation quality, and patient interaction while exploring deeper dimensions of intelligence and existence. Connect with him on LinkedIn and Instagram.
JMAI: What do you regard as a good academic paper?
Pedro Angelo: I consider a good academic paper as one that addresses a relevant research question, presents a clear and structured methodology, and contributes original insights into interdisciplinary fields. It should be well-supported by evidence, with a solid theoretical foundation and transparent data analysis. Clarity in writing is essential, and complex ideas should be communicated effectively without unnecessary jargon. Additionally, a strong paper acknowledges its limitations and discusses the broader implications of its findings. Finally, it should invite further discussion and exploration, adding value to the scientific community rather than merely presenting data.
JMAI: How do you avoid biases in one’s writing?
Pedro Angelo: Avoiding biases in academic writing involves rigorous methodology, critical self-awareness, and full transparency. A key principle is recognizing that science is inherently falsifiable, meaning our conclusions are always provisional and open to revision when new evidence emerges. This humility in knowledge encourages us to admit that we can be wrong and to embrace criticism as an opportunity to grow. Using objective, data-driven language and avoiding unfounded assumptions helps maintain balance, while considering multiple perspectives in the literature review ensures a comprehensive discussion. Employing structured methodologies, such as randomized controlled trials or blinded analyses, minimizes subjective influence. In addition, a robust peer-review process and collaboration with diverse research teams serve to identify and correct implicit biases, ultimately leading to more reliable and evolving scientific insights.
JMAI: Would you like to say a few words to other academic writers?
Pedro Angelo: Scientific progress is built on the collective effort of those who dare to question, explore, and refine knowledge. Writing an academic paper is not just about publishing results, it’s about contributing to a global conversation, where each piece of research connects with past discoveries and inspires future innovation. Challenges and setbacks are part of the journey but should be seen as steps toward deeper understanding rather than obstacles. Every well-structured study, no matter how small, has the potential to shape the future of science. To those dedicating themselves to this path: keep pushing forward, stay curious, and remember that even incremental progress can have a lasting impact.
(by Sasa Zhu, Brad Li)
Wahid Ullah
Wahid Ullah is a Lecturer in Medical Laboratory Sciences at Riphah International University, Islamabad, Pakistan. He holds an M.Phil Degree in Medical Laboratory Sciences from the University of Haripur and has extensive experience in medical diagnostics, molecular biology, and genetics. His research focuses on artificial intelligence, molecular diagnostics, and disease biomarkers. He has contributed to multiple peer-reviewed publications, including systematic reviews and studies on hematological and infectious diseases. His master's research involved the molecular characterization of SARS-CoV-2 strains, reflecting his expertise in virology and genomic analysis. He has previously worked as a Research Assistant at the Institute of Biomedical and Genetic Engineering and as a Medical Laboratory Technologist. With a strong foundation in molecular and genetics, he remains committed to interdisciplinary research. He will soon begin his PhD studies, further advancing his expertise in biomedical sciences. Connect with him on LinkedIn.
Dr. Ullah thinks a good academic paper is well-structured, evidence-based, and contributes meaningful insights to its field. It should have a clear research question, a well-defined methodology, and a logical flow that guides the reader through the study's objectives, findings, and implications. High-quality papers are rooted in rigorous research, incorporating a comprehensive literature review to contextualize researchers’ findings within existing knowledge. They should also present data transparently, ensuring reproducibility and credibility. Clarity in writing is essential, as complex ideas should be communicated concisely without ambiguity. Furthermore, a strong paper acknowledges its limitations, paving the way for future research. Ethical considerations, proper citations, and adherence to journal guidelines are also key elements that ensure scholarly integrity. Ultimately, a good paper not only advances knowledge but also inspires further inquiry and discussion within the academic community.
In Dr. Ullah’s view, researchers should maintain objectivity by using credible, peer-reviewed sources and presenting a balanced perspective to avoid bias in academic writing. He believes neutral language, methodological transparency, and clear inclusion criteria help minimize bias. Moreover, acknowledging limitations, seeking diverse feedback, and being aware of cognitive biases further enhance fairness and accuracy. Striving for intellectual honesty ensures the integrity of scholarly work.
Lastly, Dr. Ullah would like to say a few words to all academic writers, “Your dedication fuels scientific progress. Every study, no matter how small, contributes to knowledge and innovation. Stay committed, embrace challenges, and keep pushing boundaries. Your work shapes the future and inspires others. Keep going!”
(by Sasa Zhu, Brad Li)
Nino Gvajaia
Dr. Nino Gvajaia is a recent graduate of the American MD Program at Tbilisi State Medical University. She is dedicated to medical education, clinical research, and healthcare innovation. She is a Histology Lecturer and Basic Life Support Instructor at Tbilisi State Medical University and Ken Walker International University. She gained hands-on experience through clinical rotations and an observership at Emory University Hospitals in Hematology-Oncology and Neurology, as well as working as a Junior Doctor in the ICU department. She also attended the GAIN Summer School, exploring AI modeling of human cognition and emotion. Her research focuses on AI in medical diagnostics, including a study comparing GPT-4’s accuracy to physicians. Additionally, she has published work on biomarkers for early sepsis detection. Actively engaged in medical conferences, she has helped organize multiple events in Georgia. Beyond medicine, she is passionate about sculpting, painting, and writing.
In Dr. Gvajaia’s view, academic writing is more than just putting words on paper—it helps develop critical thinking, clear communication, and analytical skills. Effective writing is essential for publishing research, securing grants, and presenting work at conferences, as it significantly influences professional opportunities. Strong writing is also key for publishing research, securing grants, and presenting work at conferences, shaping professional opportunities. Beyond that, it teaches research skills, objective thinking, and ethical writing practices, ensuring credibility. Most importantly, academic writing connects individuals with the broader scholarly community, giving them a voice in important conversations and helping drive progress in their fields.
To make writing more critical, Dr. Gvajaia thinks it is essential to move beyond stating facts and actively engage with ideas. This means questioning assumptions, considering different perspectives, and backing arguments with strong evidence rather than opinions. Instead of simply summarizing sources, a critical writer examines their strengths, limitations, and relevance to the topic. A clear structure helps build a well-supported argument, while precise and objective language ensures clarity. Addressing counterarguments adds depth and demonstrates awareness of different viewpoints. Ultimately, critical writing is about thinking deeply, analyzing information carefully, and making well-reasoned arguments.
“One of the most memorable moments in my academic journey was working on our research project, Artificial Intelligence in the Medical Field: Diagnostic Capabilities of GPT-4 in Comparison with Physicians. What started as a standard study quickly grew into something much bigger than we had anticipated,” sharesDr. Gvajaia, “As we analyzed the results, we realized that GPT-4 was performing unexpectedly well, even matching human doctors in some diagnoses. The implications were significant—could AI actually support or even surpass physicians in certain areas? News of our research spread quickly, and before we knew it, several major TV channels in Georgia picked up the story. We were invited for interviews where we discussed not only our study but also the role of AI in medicine and our team’s future plans. The public reaction was a mix of excitement and concern, with discussions ranging from AI’s potential in healthcare to the possibility of it replacing doctors. Seeing our research spark debates beyond academic circles and reach mainstream media was an eye-opening experience. It reinforced the idea that academic writing isn’t just about publishing papers—it can drive conversations, shape perspectives, and influence the future of medicine.”
(by Sasa Zhu, Brad Li)
Mohammad Najeh Samara
Mohammad Najeh Samara is a PhD candidate in Systems Science and Industrial Engineering at Binghamton University, United States. His research focuses on applying machine learning, data-driven analysis, and Lean Six Sigma methodologies to drive continuous improvement in healthcare systems. He has worked extensively with UHS hospitals and veteran nursing homes on projects aimed at improving patient outcomes, enhancing recreational therapy programs, and addressing vaccine hesitancy in at-risk communities. His recent work strongly emphasizes the use of predictive modeling and machine learning techniques to support clinical decision-making and improve health outcomes. He is passionate about leveraging data-driven insights to design practical, impactful solutions that advance healthcare delivery, enhance system efficiency, and promote equitable access to quality care. Connect with him on LinkedIn.
Dr. Samara believes a good academic paper addresses a meaningful research question, applies rigorous and appropriate methodology, and clearly communicates its findings and implications. It should provide a well-grounded literature review, present data and results transparently, and offer conclusions that contribute new knowledge or practical solutions to the field. Additionally, a strong academic paper is written in a logical, cohesive structure and is accessible to both experts and those interested in the topic.
According to Dr. Samara, it is crucial to approach research with an open mind, rely on objective data, and ensure that interpretations are based on evidence to avoid biases in writing. Using multiple data sources, conducting peer reviews, and maintaining transparency in methodology can help minimize bias. Additionally, it is important to recognize one’s own assumptions and avoid language that could be leading or exclusionary. Engaging with diverse literature and perspectives also contributes to a more balanced and unbiased presentation.
“I would like to encourage all academic writers to remain persistent and passionate in their pursuit of knowledge. The process can be challenging, but every contribution, no matter how small, plays a vital role in advancing scientific understanding and improving the world around us. Stay curious, be open to feedback, and continue striving to produce work that makes a meaningful difference. Your dedication is the foundation of future innovation,” says Dr. Samara.
(by Sasa Zhu, Brad Li)
Anupama Nair
Anupama Nair is a BS/MD student at Virginia Commonwealth University Honors College, majoring in Biology and minoring in Chemistry and Pre-Medicine through the Guaranteed Medical School Admission program. An AI4ALL 2020 Alum from the University of Maryland, she has worked on several projects creating machine learning models in diagnosing and preventing Alzheimer’s disease and lung cancer.
She is a Clinical Trial Core intern at the Johns Hopkins University School of Medicine in the Department of Otolaryngology. Her research interests include biomedical optimization of head and neck cancer surgery and applying AI in head, neck, and gastrointestinal cancer prediction. At VCU, she is spearheading a biomedical project that predicts rises in intracranial pressure using various neurological markers leveraging AL/ML. This work is relevant to stroke, severe TBI, and neurocritical patients and will help to inform clinical treatment plans, preventing secondary brain injury.
From Anupama’s perspective, an essential element of a good academic paper is the ability of the paper to collect, synthesize, and form a distinct take on existing research on the given field of study. Academic papers demand that the author explore varying sides to a topic of research. A good academic paper will be able to present prior research that has been conducted in an interesting and coherent way, demonstrating not only the rationale for the proposed research, but also the existing arguments in the field in discussion with one another. It is essential to ensure that the information presented is accurate and understandable for readers, enhancing the credibility of the author(s) and establishing a solid framework for the paper.
Anupama asserts that something that may be overlooked in the preparation of a paper is the overall planning and structure of the paper itself, where authors may jump straight into writing a synthesis without having thoroughly examined the information already available. A key way to combat this is to stay organized in preparing the paper, having documented all sources used, their key points to include in the paper, and the relevance of the study to the paper itself. Engaging in this practice not only assists the author in creating a well-rounded paper, but it also boosts the writer's confidence about the topic. With a greater understanding of the subject as a whole, the writing process becomes easier.
“One thing to always keep in mind during the process of academic writing is that all good things take time. When writing papers that reflect years of work in a specific field, it is essential to ask relevant questions, gather appropriate sources, and clearly present the findings in writing. It is essential to have others in the field review the work before submission, as writers may often overlook key information or perspectives they had not previously considered. Having more eyes on a paper prior to submission is key to writing quality papers, and a hallmark of a good academic writer,” says Anupama.
(by Sasa Zhu, Brad Li)
Afiq Izzudin A. Rahim
Dr. Afiq Izzudin A. Rahim is a medical lecturer and public health physician at the Department of Community Medicine, Health Campus, Universiti Sains Malaysia (USM). He also serves as the Deputy Coordinator of the Digital Health Unit, School of Medical Sciences, USM, where he leads efforts in advancing digital health innovation through the DIGIMED@USM initiative. His primary research interests focus on digital health, health quality management, occupational health, and public health systems. He is deeply engaged in teaching medical and postgraduate students while championing the integration of AI-powered technologies into healthcare. His recent projects include developing large language models for clinical use at USM, applying machine learning to predict hospital length of stay in Kelantan, and deploying telemedicine applications in disaster settings. He is also an aspiring digital health entrepreneur, working towards building a globally recognized health tech start-up. Connect with him on LinkedIn.
Dr. Rahim believes an impactful academic paper begins with a meaningful question and ends with insights that matter. It is not just about data; it is about clarity, rigor, and relevance. A well-structured paper that tells a coherent story, supported by solid methodology and sound analysis, stands out. It should provide something new, such as a fresh perspective, a practical application, or an inspiration for future research. A good paper values the reader's time and intellect, clearly communicates complex ideas, and openly acknowledges its limitations. A truly impactful paper is one that advances the field while remaining grounded in ethical scholarship and purpose.
In Dr. Rahim’s view, writing for publication requires more than just reporting findings. It demands clarity, discipline, and responsibility. Authors should begin with a strong understanding of their research question and ensure their study design addresses it appropriately. Throughout the process, it is essential to maintain transparency, uphold ethical standards, and stay grounded in evidence. They should pay close attention to the journal’s guidelines, structure arguments logically, and avoid unnecessary jargon; cite sources responsibly and reflect on their findings and significance; stay open to feedback, revise humbly, and remember that publication is a privilege, not merely a goal.
“For me, academic writing is both a calling and a commitment. I am deeply motivated by the belief that knowledge, when shared purposefully, can create real change, whether in policy, practice, or education. Each manuscript is a way to contribute to the global conversation in health, public service, and science. Beyond professional growth, I find joy in mentoring others, especially students and early-career researchers, through the writing process. Spiritually, I also view writing and research as forms of service, contributing to society and leaving a legacy of knowledge. The effort is demanding, but the reward of seeing your work inform, inspire, or improve outcomes is worth every moment,” says Dr. Rahim.
(by Sasa Zhu, Brad Li)
Elad Shvartz
Elad Shvartz recently graduated from the MD program of Bar-Ilan University and is currently working as a medical intern at the Kaplan Medical Center in Rehovot, Israel. Most of his research in the last two years focused on recently available AI tools, like ChatGPT. As these tools evolved, he began comparing their efficacy against each other in various medical tasks, simulating expert doctors, residents, and patients. He published several benchmarking studies, assessing different aspects of their functionalities in different methodologies. More recently, he began focusing on the development side of AI oriented for image processing, for diagnostics in the field of ophthalmology. He is passionate about AI, believing it will integrate into various fields of medicine. Understanding how to work with this rapidly evolving technology is crucial for its successful utilization.
JMAI: What are the essential elements of a good academic paper?
Dr. Shvartz: I believe in simplicity. A good academic paper should present a clear research question and a straightforward methodology, without unnecessary complexity. Communicating the outcomes clearly is critical. Usually, over-complicating the methods or cluttering the discussion with many points often obscures the main message. Equally essential is presenting data graphically, in a simple and insightful manner, as effective visuals enable readers, especially clinicians, to quickly grasp the key findings and implications. Overall, the easier it is to digest the findings, the more confident the reader will be in applying the paper’s insights. Ultimately, a good paper provides practical value, clearly conveying how the research can directly improve clinical judgments, such as selecting the optimal diagnostic method or understanding the strengths and limitations of therapeutic options.
JMAI: What should authors keep in mind while preparing a paper?
Dr. Shvartz: Authors should always keep their target audience clearly in mind. Clinicians in particular usually value actionable conclusions they can apply in practice, findings that explicitly demonstrate how a paper’s findings make decision-making easier in the real world. It’s critical to prioritize simplicity and readability while maintaining methodological rigor and transparency, as readers depend on these to trust, interpret, and apply the findings. Authors should consider how readers will visually engage with their paper. Using effective visuals helps authors present complex data effectively and increases a paper's impact.
JMAI: Would you like to say a few words to encourage other academic writers who have been devoting themselves to advancing scientific progress?
Dr. Shvartz: Academic writing is challenging, but it is among the most impactful ways to contribute meaningfully to scientific and clinical advancement. Every well-crafted paper has the potential to influence practice by simplifying complex evidence, refining diagnostic methods, or making therapeutic decisions easier. Remember that clarity, simplicity, and methodological rigor are your goals – always strive to achieve them. By clearly presenting your data, you help others quickly integrate new knowledge into daily clinical practice. Stay encouraged, knowing that producing quality research ultimately translates into better patient outcomes and continuous improvement in healthcare.
(by Sasa Zhu, Brad Li)
Hang Dao Viet
Dr. Dao Viet Hang (Assoc. Prof, MD, PhD) graduated from the Hanoi Medical University in 2011 and got her PhD degree in 2016. She is a skilled gastroenterologist and hepatologist, as well as a clinical researcher and lecturer at Hanoi Medical University. She is now the Vice General Secretariat of the Vietnam Association of Gastroenterology and the Vietnam Association for the Study of Liver Diseases, and Director of Endoscopic Centre, Hanoi Medical University Hospital. She is interested in liver cancer, HBV, gastrointestinal endoscopy, functional disorders, and the application of AI in endoscopy. She believes that utilizing AI in endoscopy is a promising research direction that can assist doctors during endoscopic procedures. She has experience participating in many AI projects, where she leads her team to recruit, label data, validate the product, and implement clinical studies. Her projects focus on developing AI to detect upper GI tract cancer and colorectal polyps in GI endoscopy. Connect with her on LinkedIn.
From Dr. Hang’s perspective, academic writing serves as a vital instrument for scientists to convey their investigations, exploration, and insights within their expertise. It functions as a standardized tool for clearly presenting methodologies and findings, as well as for sharing ideas, engaging in scholarly debate, and proposing future research directions. During the writing process, researchers develop arguments and counterarguments, enabling them to enhance their understanding of their professional fields and improve their multidimensional thinking. This process not only enhances individual knowledge but also contributes to collective intelligence. Additionally, academic writing enables other researchers to access foundational knowledge, adopt analytical approaches, understand emerging trends, and foster their own research paths, thus accelerating the evolution of scientific domains. In conclusion, academic writing is more than a medium of expression; it is the cornerstone of sustainable progress in science and technology.
In the era of rapid evolution of science and technology, Dr. Hang thinks the key to staying up-to-date and innovative for a medical researcher is the formulation of a well-defined research question. Such questions should stem from experience-based observations grounded in clinical practice, especially in the Vietnamese context, where the diversity of patients and diseases offers a rich foundation for inquiry. Besides, through specialized research literature, attending academic conferences, and networking, she continuously seeks out the promising topics that are poised to shape the field of gastroenterology and hepatology over the next 5 to 10 years. This process helps her identify knowledge gaps as well as feasible research directions to optimize resource utilization and enhance the quality of healthcare delivery that is contextually appropriate for Vietnam. For instance, the integration of AI in gastrointestinal endoscopy represents promising yet underexplored areas with significant potential for advancement in Vietnam.
Dr. Hang believes that the medical profession is inherently challenging, involving clinical responsibilities as well as obligations in education and research. Without commitment, perseverance, and genuine passion, it is easy to feel overwhelmed, and the development of novel and transformative research directions that truly benefit patients remains unattainable. Especially in Vietnam, conducting research still faces significant challenges due to limited resources, funding, and personnel. Clinical research provides the data needed to support changes and improvements in treatment delivery. Additionally, the process of academic writing facilitates a space for reflection. It provides an opportunity to pause, critically evaluate, refine her knowledge, sharpen her mind, and synthesize insights drawn from observation and experience. This process is essential for addressing complex real-world healthcare problems.
(by Sasa Zhu, Brad Li)
Iliyas Ibrahim Iliyas
Dr. Iliyas Ibrahim Iliyas is a lecturer from the Department of Computer Science at the University of Maiduguri and a PhD scholar at Abubakar Tafawa Balewa University. His research areas are machine learning, data science, artificial intelligence, and software development. His recent projects include recent trends in prediction of chronic kidney disease using different learning approaches: a systematic literature review.
Dr. Iliyas considers academic writing a major channel for scientists to report and document their methods, results, and interpretations in a well-structured manner. He believes evidence synthesis begins with a focused research question, a systematic search, and exclusion criteria for study design, population, and outcomes when concluding writing. Furthermore, he points out that following reporting guidelines ensures comprehensive reporting, which facilitates efficient peer-review indexing and assists readers in assessing the validity and applicability of research.
(by Sasa Zhu, Brad Li)
Matthew Kaufman
Dr. Matt Kaufman is currently the Chief Resident for Stanford University’s Physical Medicine and Rehabilitation Residency Program and is an avid researcher in Sports and Spine Medicine. He also works with the Stanford Lifestyle Medicine group to craft additional content helping older adults boost their longevity. He has a couple of different research interests, including human performance, longevity, lifestyle medicine, implementing technology into medical practice, and outcomes from spine medicine procedures. He is currently researching how to predict and prevent falls for prone adults to minimize their risks.
According to Dr. Kaufman, academic writing is representative of both the history and future of science and medicine. This text builds on citations and develops a clear argument. It illustrates the historical context of various topics and shows how new information can either support or challenge established ideas. Additionally, it raises new questions that others might explore in the future. In that sense, it can be incredibly collaborative and bring scientific communities together to try and answer questions, solve problems, and understand more about the world.
By staying up to date with writing, Dr. Kaufman thinks the best way is to stay up to date with the current literature. It sounds repetitive, but, in a sense, researchers must understand the current status of literature in their topic to know what questions have been answered and what needs answering. With any paper he writes, his first task is understanding what is currently out there and seeing if his idea for a new project is worth pursuing or not. He adds, “It is crucial to read papers routinely, subscribe to journals that are interesting, and attend national meetings to understand what is being done!”
“I have genuine curiosity and desire to understand more about the topics I am writing about. Passion can arise from various sources; it may stem from previous papers, discussions with colleagues, or directly from patients and their inquiries. I think that the majority of my passion, though, comes from advancing care for my patients. There is no better feeling than being able to tell a patient that I have personally investigated their question and that I can answer it to the best of my ability. Being able to communicate my findings to others and contribute to patient care is one of the most fulfilling ways I can spend my professional time,” says Dr. Kaufman.
(by Sasa Zhu, Brad Li)
Sasanka Katreddi
Dr. Sasanka Katreddi, PhD, is an AI researcher, currently serving as a Data Scientist at Daimler Truck North America, USA. Her research interests span predictive modelling, advanced machine learning techniques, and GenAI, including developing LLMs for industrial applications. She has significant expertise in applying machine learning algorithms to real-world time-series telemetry and automotive datasets. Her work focuses on leveraging AI/ML to solve complex problems in the automotive domain, using applications like fuel consumption prediction and emission estimation. Additionally, she has extended her research to explore alternative fuel vehicles in the heavy-duty sector, promoting the adoption of low/zero-emission technologies for sustainable transportation. She has contributed to AI in the medical/health domain using images for the early detection of pneumonia. She actively stays engaged with the latest advancements in AI research to continuously enhance her work and its real-world impact. Connect with her on LinkedIn.
Dr. Katreddi thinks a good academic paper combines clarity, depth, and originality to contribute meaningfully to its field. It begins with a clear purpose, presenting a focused research question or hypothesis that addresses a relevant problem. A strong introduction and literature review provide context, showing how the work builds on and advances existing knowledge. The methodology is transparent and rigorous, enabling reproducibility. Results are presented clearly, supported by relevant data and visualizations, and followed by a critical discussion that interprets findings, acknowledges limitations, and explores broader implications. The writing is concise and precise, making complex ideas accessible without sacrificing depth. Above all, the paper offers an original contribution—whether a new method, insight, or application—that pushes the field forward. Logical flow ensures coherence from start to finish, while proper referencing gives due credit to prior work. A well-crafted title and abstract capture attention, inviting readers to engage with and build upon the work. A well-written academic paper facilitates research advancement and greatly impacts the community.
In Dr. Katreddi’s view, an effective author combines critical thinking with clear communication to convey ideas in a meaningful way. They possess strong research skills, enabling them to find, understand, and integrate relevant literature and data. Their writing is structured and logical, ensuring that ideas flow coherently across sections. Attention to detail is essential, as it ensures accuracy in language, data, and references. Creativity and originality allow authors to bring fresh perspectives to their work, while technical expertise lends authority to their writing. Persistence and discipline are equally important, helping authors refine their work through revisions and meet deadlines consistently. Ethical awareness ensures academic integrity through proper citation and responsible reporting of findings. Finally, adaptability allows authors to tailor their tone and style to suit different audiences, journals, or communication formats. These skills enable authors to write clearly and contribute meaningfully to their field.
Dr. Katreddi believes that academic writing is crucial in shaping her PhD journey. Ensuring her work is readable and understandable for a diverse audience is always challenging. Academic writing involves both passion and challenge, transforming complex ideas into clear, impactful narratives, especially following the guidelines and sticking to the word count. To her, writing regularly, at least for an hour a day, has built clarity and made the publication process smoother.
(by Sasa Zhu, Brad Li)
Yong Bae Kim
Dr. Yong Bae Kim, MD, is a general surgeon and endoscopist with more than 15 years of experience, working at the Korea Association of Health Promotion, Jeju Branch. Trained in both clinical medicine and data science, he enjoys combining advanced IT with endoscopic techniques. His research centers on two pillars of colonoscopy safety: procedural and oncologic safety. For procedural safety, he studies the colon’s three-dimensional (3D) anatomy which can make procedures faster and safer. For oncologic safety, he designs methods to ensure we catch more precancerous polyps during colonoscopy—such as a smartphone-based deep-learning system that identifies polyps in real time. Each project starts from his commitment to safer, more effective colonoscopy and to translating cutting-edge AI into practical, low-cost tools for everyday practice.
Dr. Kim thinks a good paper shows new possibilities in the AI era. Technology moves so quickly that waiting for a “perfect” study can make the idea old-fashioned before it appears. Instead, researchers should offer a clear concept early—supported by solid evidence—so others can build on it. When an idea reaches many people, something like a “Large Human Model”, driven by collective insight, can grow as fast and as powerfully as today’s “LLM (Large Language Models)”.
Dr. Kim believes that endless curiosity is essential for authors; however, it is equally important for them to begin with what they have. He follows the MVP principle: create a Minimal Valuable Product rather than waiting for ideal conditions. If high-quality local data are scarce, look for public datasets, clean them, and show a first result. Flexibility, rapid learning, and steady integrity let a single researcher turn limited resources into actionable clinical insights.
“I chose JMAI for three reasons. First, it offers an unusually fast route from submission to publication—a vital advantage for independent researchers like me who need to share smaller-scale studies quickly. Second, although the journal was not yet indexed in SCIE when I submitted, I discovered that it was supported by Tencent—one of the world’s largest technology companies—and dedicated exclusively to Medical Artificial Intelligence. This unique partnership convinced me that the journal held exceptional promise and would soon gain broad recognition. Finally, the review process was exceptionally thorough; the reviewers provided deep, constructive feedback that strengthened my manuscript and solidified my confidence in JMAI,” says Dr. Kim.
(by Sasa Zhu, Brad Li)
Vinicius Anjos de Almeida
Dr. Vinicius Anjos de Almeida is a family physician and PhD candidate in Artificial Intelligence and Healthcare at the University of São Paulo, Brazil. After completing his medical degree and residency at the same institution, he served as a preceptor in the family medicine program. His research focuses on automating medical coding using deep learning, combining language models, semantic search, and reinforcement learning. He holds a professional certification in Deep Learning from MITxPRO and has applied machine learning to problems ranging from clinical code selection to medical image classification. Vinicius has led AI development in both academic and industry settings, including projects involving LLMs for electronic health records and chatbot tools based on national guidelines. He has presented at international conferences and published in peer-reviewed journals. His goal is to advance clinically relevant AI systems that support healthcare delivery. Connect with him on LinkedIn.
Dr. de Almeida believes that a strong academic paper begins with a clearly defined and well-structured research question. Clarity about the problem being addressed is essential—not only for guiding the research process but also for communicating its relevance. He thinks the best academic papers are those rooted in a genuine intent to benefit others, even if the connection to real-world impact is not immediately visible in technical fields. When researchers care deeply about the question they are trying to answer, they are more likely to pursue the most rigorous and ethical methods available. This results in a paper that is both methodologically sound and meaningful. In that sense, producing a high-quality paper becomes a natural outcome of purposeful, well-motivated research.
In Dr. de Almeida’s opinion, key skill sets of a good author include intellectual humility and a strong ability to learn efficiently. Contributing to human knowledge requires being more of a learner than a teacher, especially as knowledge becomes increasingly complex. Identifying the most important topics to learn and eliminating distractions is essential. Clear goal-setting is another important skill. When authors know what they are aiming to contribute, it becomes easier to make consistent, purposeful decisions throughout the research and writing process. Equally important is the ability to adopt the reader’s perspective: asking, “Why should someone trust what I have written?” This mindset naturally leads to more rigorous arguments and transparent reasoning. Seeking feedback, asking for help, and collaborating with others are also essential. Research is rarely a solitary endeavor; significant work often emerges from strong, open collaboration.
“I have a story that highlights the importance of resilience in academic writing: early in my PhD, I started a scoping review project with a broad research question. As the work progressed, we encountered methodological issues—mainly that the scope was too wide and the inclusion criteria captured too many articles, making the results difficult to synthesize. Although it became a useful chapter in my thesis, I was not fully satisfied with the outcome. Rather than giving up on the topic, I decided to refine the research question and try again. I also took the opportunity to invite collaborators to join me. To my surprise, the project grew significantly—we now have 23 researchers from 8 countries involved. The new version of the review is much stronger and will be submitted for peer review soon,” says Dr. de Almeida.
(by Sasa Zhu, Brad Li)
Srinivasa Ramanujan Boora
Dr. Srinivasa Ramanujan Boora is an Assistant Professor of Medicine at Penn State Health Holy Spirit Medical Center. His primary research interests lie at the intersection of obesity, digestive diseases, and the burgeoning field of artificial intelligence in medicine. His recent projects have focused on understanding healthcare providers' perceptions of artificial intelligence in clinical settings, as well as exploring the application of AI for the detection and management of medical conditions such as atrial fibrillation. His work aims to leverage technological advancements to improve patient care and medical understanding.
Dr. Boora thinks academic writing is indispensable for the advancement of science and knowledge. Its importance stems from several critical functions: it serves as the primary mechanism for disseminating new discoveries, research findings, and theoretical frameworks to the broader scientific community and beyond. Through the rigorous process of academic writing, authors are compelled to refine their understanding, critically analyze data, and develop robust arguments, thereby enhancing their own analytical and critical thinking skills. Ultimately, academic writing ensures that validated information is systematically shared, building a cumulative body of knowledge that underpins all scientific and intellectual progress.
From Dr. Boora’s perspective, it is now considered crucial for authors to share their research data. This practice is essential for upholding the core principles of the scientific method. Sharing open data allows for independent verification and reproducibility of findings, which significantly boosts the credibility, integrity, and trustworthiness of research. Furthermore, openly available data acts as a powerful catalyst for accelerating scientific progress; it enables other researchers to conduct new analyses, combine diverse datasets for novel insights, and build upon previous work without the prohibitive costs and time associated with data recollection. Data sharing also fosters a culture of greater collaboration and transparency within the scientific community, maximizes the value and impact of publicly funded research, and is increasingly becoming a mandatory requirement for publication in leading scientific journals and for securing grants from major funding agencies. While recognizing the significant challenges related to privacy, ethical considerations, and proper attribution, the global trend towards data sharing is a vital step in creating a more robust, efficient, and reliable scientific ecosystem.
“To all academic writers and researchers dedicating yourselves to the tireless pursuit of knowledge and truth: your dedication is the very fuel that propels the engine of discovery. Every paper, every experiment, and every meticulously crafted argument you produce contributes to building a taller ladder for humanity to ascend, broadening our collective understanding of the world. Your work is not merely an intellectual exercise; it is a vital and invaluable contribution to our shared future. Thank you for your unwavering commitment and tireless pursuit of knowledge and truth,” says Dr. Boora.
(by Sasa Zhu, Brad Li)
Ashkan Fakharifar
Dr. Ashkan Fakharifar earned his MD from Islamic Azad University, Iran, in 2021 and worked as an emergency physician in the Emergency Department of Vali‑e‑Asr Hospital until the end of 2024. He is now focusing on Diagnostic Radiology and the integration of artificial intelligence (AI) and machine learning (ML) into healthcare. His recent work involves medical image processing, Python programming, and applying ML techniques in diagnostic radiology to enhance accuracy and efficiency. He is enthusiastic about the use of AI in medicine, particularly in radiology, and believes it represents the future of healthcare. With AI's support, the future of medicine could be extraordinary for both healthcare providers and patients.
Dr. Fakharifar believes that academic writing is essential in today's world because it enables researchers to communicate knowledge in a clear, structured, and reliable manner. It ensures that research findings are presented with accuracy and an evidence-based approach, allowing others to verify results and build or test new hypotheses. Academic writing advances science and medicine by promoting critical thinking and ethical responsibility. Its standardized format helps establish credibility while preventing misinformation and plagiarism. In medicine, it plays a crucial role in transferring new discoveries that improve patient care and clinical practice. Academic writing also opens doors for worldwide collaboration and future research opportunities. It is not just about testing hypotheses and documenting results, but about advancing knowledge responsibly and helping shape the future of the field.
Dr. Fakharifar thinks that an author carries a great responsibility. He or she should double‑check all data and results, avoid misinformation, and present only the truth. If data are collected from patients, the author must also guarantee privacy and confidentiality. Writing should always be unbiased, reflecting facts rather than personal preferences or opinions. It is equally important to avoid plagiarism, uphold integrity, and accept full responsibility for one’s work. A great author also needs curiosity and creativity to generate new ideas and hypotheses, develop innovative methods, and advance knowledge. Collaboration is crucial when working with co‑authors, team members, and peer reviewers, since academic writing often requires multiple revisions and careful attention to detail. Above all, a good author must remain committed to ethical responsibility and to advancing knowledge in their field.
Dr. Fakharifar emphasizes that data sharing is essential for authors, particularly given the rapid pace of publishing and the growing influence of chatbots like ChatGPT. Some authors now rely on AI-generated content, and hallucinations can produce unreliable or even non-existent results. Without transparency, such issues may go unnoticed, reducing trust in academic communities. Data sharing in machine learning and AI enables researchers to test and compare models, validate code, and enhance accuracy. It also brings transparency and reproducibility, enabling others to verify findings, test new hypotheses, and build upon previous work. At the same time, authors must uphold ethical responsibility by protecting patient confidentiality and complying with data privacy regulations. Responsible data sharing, therefore, strengthens trust, ensures integrity, and advances scientific knowledge.
(by Sasa Zhu, Brad Li)