Implementing an artificial intelligence system to comprehensively manage people with glaucoma: a blueprint
Letter to the Editor

Implementing an artificial intelligence system to comprehensively manage people with glaucoma: a blueprint

Simon E. Skalicky1, Robert N. Weinreb2, Nahum Goldmann3, Ricardo Augusto Paletta Guedes4, Christophe Baudouin5, Xiulan Zhang6, Aukje van Gestel7, Eytan Z. Blumenthal8, Paul L. Kaufman9, Robert Rothman10,11,12, Ana Maria Vasquez13, Paul Harasymowycz14, Derek S. Welsbie2, Ivan Goldberg15,16

1The Department of Surgery Ophthalmology, University of Melbourne, Melbourne, VIC, Australia; 2Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, CA, USA; 3ARRAY Development, Ottawa, ON, Canada; 4Paletta Guedes Eye Institute and Federal University of Juiz de Fora, Juiz de Fora, Brazil; 5Quinze-Vingts National Ophthalmology Hospital, and Vision Institute, IHU ForeSight, Paris, France; 6Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China; 7Studio van Gestel, Helmond, The Netherlands; 8Department of Ophthalmology, Rambam Health Care Campus, Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel; 9Department of Ophthalmology & Visual Sciences, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA; 10Eye Care Associates & Glaucoma Consultants of Long Island, Bethpage, NY, USA; 11Department of Ophthalmology, Zucker School of Medicine at Hofstra/Northwell, West Hempstead, NY, USA; 12InFocus Capital Partners, Jericho, NY, USA; 13Instituto de Oftalmología y Glaucoma Vásquez, Hospital Metropolitano, Quito, Ecuador; 14University of Montreal, Bellevue Ophthalmology Clinics and Montreal Glaucoma Institute, Montreal, QC, Canada; 15Discipline of Ophthalmology, The University of Sydney, Sydney, NSW, Australia; 16Glaucoma Unit, Sydney Eye Hospital and Eye Associates, Sydney, NSW, Australia

Correspondence to: Simon E. Skalicky, FRANZCO, PhD. The Department of Surgery Ophthalmology, University of Melbourne, 2/232 Victoria Pde East, Melbourne, VIC 3002, Australia. Email:

Response to: Yoo TK. Actions are needed to develop artificial intelligence for glaucoma diagnosis and treatment. J Med Artif Intell 2023;6:11.

Received: 02 August 2023; Accepted: 08 September 2023; Published online: 10 October 2023.

doi: 10.21037/jmai-23-91

We thank Dr. Yoo for his comments (1). Our recent article, “Defining functional requirements for a patient-centric computerized glaucoma treatment and care ecosystem” is a blueprint for implementing a worldwide artificial intelligence (AI) system that comprehensively and holistically evaluates and manages people with glaucoma (2). It considers the multiple types of glaucoma, different requirements at various disease stages, managing diagnostic uncertainty, the need for serialised monitoring over time, the pros and cons of treatment including the problems of over- and under-treatment, as well as placing glaucoma in the context of other chronic illnesses, healthcare economic constraints, psychosocial considerations and of maintaining patients’ quality of life.

With a globally ageing population, a substantial increase in longevity with chronic disease, insufficient healthcare staff, and increasingly constrained health budgets, patients, healthcare providers and funders are looking to reduce the cost and burden of managing numerous chronic diseases (3,4). In the future, AI-driven clinical diagnostic and management tools will reduce the cost, the travel and the staff hours required to manage chronic illnesses, as well as patients’ burden, freeing up precious healthcare resources for more urgent issues, or unstable phases of chronic diseases (5).

Dr. Yoo is correct in that today, with the principal architecture of this critical system defined, urgent action is needed. The call-to-action is strong, while the task is big. There will be obstacles—both ones we can predict now and others unknown. It may take years, decades even, to bear fruitful results. So, the time to start is now.

A huge volume of data is required to build AI-based models to describe multiple variations in outcomes and to support patients in ongoing home management of their chronic diseases. It is critical to collect the right kind of healthcare data globally and from a variety of sources, over a long time (6-8).

A broad consortium of stakeholders is required to build consensus, generalisability and transferability across different cultures, healthcare models, regulatory and funding environments (9). This will necessitate leveraging current socio-economic and healthcare networks, as well as forging deeper and new networks that include healthcare providers and chronic patients. To ensure genuine progress, strong global reach leadership is needed.

Fortunately, there exists a robust, multifaceted global network of glaucoma specialists, the World Glaucoma Association, in which many of our co-authors are closely involved. Other groups to provide critical input would include patient representative associations, clinicians (from both ophthalmology and optometry), funders, the health insurance industry, and other health tech interest groups.

There are many potential leaders in implementing these initiatives including industry, global big tech (the current owners of most modern AI systems required for this undertaking), electronic medical record providers and ophthalmic diagnostic companies, many of which are integrating AI or already have done so into their diagnostic solutions. Governmental and intergovernmental organizations, which could in turn involve top healthcare system integrators that would be capable of handling such a mammoth worldwide task, could also have an important role. Such organisations include the World Health Organisation (more specifically its Digital Health and Innovation Department) and the National Institute of Health in the USA.


Funding: None.


Provenance and Peer Review: This article was commissioned by the editorial office, Journal of Medical Artificial Intelligence. The article did not undergo external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at SES discloses that he has received honoraria from Allergan, Alcon and Glaukos, and he is a director of Eyeonic Pty Ltd., which develops and provides online visual assessment applications for use on personal devices. CB declares receiving grants and contracts from Horus Pharma, Santen and Thea; consulting fees from Abbvie, Alcon, Horus Pharma, Oculis, Santen and Thea; and participation on a data safety monitoring boards or advisory boards with Thea, Oculis and Santen. RR declares that he has received honoraria for speaking at promotional events sponsored by Allergan, which sells pharmaceuticals for the treatment of glaucoma, and he is a Co-Founder and Co-Managing Member of a venture capital fund that has investments within companies that are focused on the treatment of glaucoma. PH declares receiving payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Abbvie, Alcon, JandJ Vision, Bausch and Lomb, Glaukos, Zeiss, Labtician and Thea. None of the aforementioned activities or relationships causes a conflict of interest in the matter of this paper. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See:


  1. Yoo TK. Actions are needed to develop artificial intelligence for glaucoma diagnosis and treatment. J Med Artif Intell 2023;6:11. [Crossref]
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doi: 10.21037/jmai-23-91
Cite this article as: Skalicky SE, Weinreb RN, Goldmann N, Paletta Guedes RA, Baudouin C, Zhang X, van Gestel A, Blumenthal EZ, Kaufman PL, Rothman R, Vasquez AM, Harasymowycz P, Welsbie DS, Goldberg I. Implementing an artificial intelligence system to comprehensively manage people with glaucoma: a blueprint. J Med Artif Intell 2023;6:17.

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