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Augmented and Artificial Intelligence in Ophthalmology
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Augmented and Artificial Intelligence in Ophthalmology

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Ophthalmology".

Deadline for manuscript submissions: 30 December 2025 | Viewed by 991

Special Issue Editors

Dr. Tina Felfeli

E-Mail Website
Guest Editor
Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON, Canada
Interests: prediction models; retinal diseases
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Edsel B. Ing

E-Mail Website
Guest Editor
Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, AB T5H 3V9, Canada
Interests: prediction models; orbital and eyelid tumours; thyroid-associated orbitopathy; oculoplastics; strabismus surgery; neuro-ophthalmology
Special Issues, Collections and Topics in MDPI journals
Dr. David Jose Mathew

E-Mail Website
Guest Editor
Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON M5S 1A1, Canada
Interests: glaucoma; ophthalmology; glaucoma imaging; animal models of glaucoma; cytokines
Special Issues, Collections and Topics in MDPI journals
Dr. Michael Balas

E-Mail Website
Guest Editor
Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON M5S 1A1, Canada
Interests: ophthalmology; artificial intelligence; data science; biostatistics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, artificial intelligence has begun to play a pivotal role in various medical fields; ophthalmology is no exception. This Special Issue, “Augmented and Artificial Intelligence in Ophthalmology”, aims to capture the current landscape and future potential of AI applications for eye health. From automated retinal screening processes and machine learning models predicting the progression of ocular conditions to AI-driven decision support systems in clinical settings, this Special Issue will provide a comprehensive overview of the clinical implications of AI in ophthalmology. Through rigorous, peer-reviewed contributions, this collection will serve as a crucial resource for ophthalmologists, researchers, data scientists, and healthcare professionals interested in the nexus of artificial intelligence and eye health.

You may choose our Joint Special Issue in JCTO.

Dr. Tina Felfeli
Prof. Dr. Edsel B. Ing
Dr. David Jose Mathew
Dr. Michael Balas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • ophthalmology
  • eye health
  • vision
  • teleophthalmology

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Published Papers (2 papers)

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Review

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25 pages, 541 KB  
Review
Augmented Decisions: AI-Enhanced Accuracy in Glaucoma Diagnosis and Treatment
by Marco Zeppieri, Caterina Gagliano, Daniele Tognetto, Mutali Musa, Alessandro Avitabile, Fabiana D’Esposito, Simonetta Gaia Nicolosi and Matteo Capobianco
J. Clin. Med. 2025, 14(18), 6519; https://doi.org/10.3390/jcm14186519 - 16 Sep 2025
Viewed by 331
Abstract
Glaucoma remains a leading cause of irreversible blindness. We reviewed more than 150 peer-reviewed studies (January 2019–July 2025) that applied artificial or augmented intelligence (AI/AuI) to glaucoma care. Deep learning systems analyzing fundus photographs or OCT volumes routinely achieved area-under-the-curve values around 0.95 [...] Read more.
Glaucoma remains a leading cause of irreversible blindness. We reviewed more than 150 peer-reviewed studies (January 2019–July 2025) that applied artificial or augmented intelligence (AI/AuI) to glaucoma care. Deep learning systems analyzing fundus photographs or OCT volumes routinely achieved area-under-the-curve values around 0.95 and matched—or exceeded—subspecialists in prospective tests. Sequence-aware models detected visual field worsening up to 1.7 years earlier than conventional linear trends, while a baseline multimodal network integrating OCT, visual field, and clinical data predicted the need for incisional surgery with AUROC 0.92. Offline smartphone triage in community clinics reached sensitivities near 94% and specificities between 86% and 94%, illustrating feasibility in low-resource settings. Large language models answered glaucoma case questions with specialist-level accuracy but still require human oversight. Key obstacles include algorithmic bias, workflow integration, and compliance with emerging regulations, such as the EU AI Act and FDA GMLP. With rigorous validation, bias auditing, and transparent change control, AI/AuI can augment—rather than replace—clinician expertise, enabling earlier intervention, tailored therapy, and more equitable access to glaucoma care worldwide. Full article
(This article belongs to the Special Issue Augmented and Artificial Intelligence in Ophthalmology)
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11 pages, 222 KB  
Perspective
Oculoplastics and Augmented Intelligence: A Literature Review
by Edsel Ing and Mostafa Bondok
J. Clin. Med. 2025, 14(19), 6875; https://doi.org/10.3390/jcm14196875 - 28 Sep 2025
Abstract
Artificial intelligence (AI) and augmented intelligence have significant potential in oculoplastics, offering tools for diagnosis, treatment recommendations, and administrative efficiency. This article discusses current and potential applications of AI in ptosis, eyelid and conjunctival cancer, thyroid-associated orbitopathy (TAO), giant cell arteritis (GCA), and [...] Read more.
Artificial intelligence (AI) and augmented intelligence have significant potential in oculoplastics, offering tools for diagnosis, treatment recommendations, and administrative efficiency. This article discusses current and potential applications of AI in ptosis, eyelid and conjunctival cancer, thyroid-associated orbitopathy (TAO), giant cell arteritis (GCA), and orbital fractures. AI-based programs can assist in screening, predicting surgical outcomes, and improving patient care through data-driven decisions. Privacy concerns, particularly with the use of facial and ocular photographs, require robust solutions, including blockchain, federated learning and steganography. Large generalizable datasets with adequate validation are crucial for future AI development. While AI can assist in clinical decision-making and administrative tasks, physician oversight remains critical to prevent potential errors. Large language models like ChatGPT also have the potential to counsel patients, although further validation is needed to ensure accuracy and patient safety. Ultimately, AI should be regarded as an augmentative tool that supports, rather than replaces, physician expertise in oculoplastic care. Full article
(This article belongs to the Special Issue Augmented and Artificial Intelligence in Ophthalmology)
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