Artificial Intelligence and the Eye

Overview

In April, 2018, the FDA approved a cloud-based software program (IDx-DR) that uses Artificial Intelligence (AI) to provide a screening decision in diabetic retinopathy without the need for a clinician to interpret the image or results. AI is now being used routinely for the rapid, accurate, and objective diagnosis of eye disease. This multidisciplinary conference will update the clinician on the current state of AI in ophthalmology and optometry, as well as highlight promising areas of research and development. It will be followed by a gala dinner in honour of the St John of Jerusalem Eye Hospital. Guests who purchase dinner tickets will receive a charitable tax receipt from St John Ambulance Canada (Registered Charity #89903 4730 RR0001).

ABOUT THE ST JOHN of jerusalem EYE HOSPITAL GROUP

This conference is part of a series hosted by the Ophthalmic Association of the St John of Jerusalem Eye Hospital Group (SOA). Established in 2015, the SOA supports the postgraduate activities of the St John of Jerusalem Eye Hospital. The SOA is a global network comprised of 5 hubs and 10 chapters, led by Mr. David Verity, Moorfields Eye Hospital, London, UK. The SOA unites professionals from all walks of life in support of the humanitarian work of the Order of St John.

All proceeds from the conference and gala dinner will go towards the St John of Jerusalem Eye Hospital, which celebrated its 140th anniversary in 2022.

ABOUT the st john of jerusalem eye hospital group ophthalmic association

Speakers and Topics

Asim Ali, MD FRCSC

Ophthalmologist-in-Chief, Hospital for Sick Children, Toronto

AI in Pediatric Ophthalmology

Michael Balas, BHSc (Supervisors: Rajeev Muni, MD FRCSC and Matthew Schlenker, MD MSc FRCSC)

Third Year Medical Student, Temerty Faculty of Medicine, University of Toronto

AI in Eye Surgery: Establishing Surgical Learning Curves &

Optical Character Recognition with Deep Learning for Automated Data Extraction of Macular Cube Spectral Domain Optical Coherence Tomography Data

Nishaant Bhambra, MD CM (Supervisor: Matthew Schlenker, MD MSc FRCSC)

Glaucoma and Advanced Anterior Segment Surgery Research Fellow, University of Toronto

Integrating AI Into Clinical Practice

Netan Choudhry, MD FRCSC DABO

Lecturer, Ophthalmology and Vision Sciences, University of Toronto; Medical Director, Vitreous Retina Macula Specialists of Toronto

AI-Based Image De-Noising

Tina Felfeli, MD

Resident (PGY1), Ophthalmology & Vision Sciences, University of Toronto; Integrated Physician-Scientist Training Program, University of Toronto

AI in population and personalized ophthalmology

Joshua Herman, BSc (Supervisor: Rajeev Muni, MD FRCSC)

Fourth Year medical student, Temerty Faculty of Medicine, University of Toronto

Optical Character Recognition with Deep Learning for Automated Data Extraction of Macular Cube Spectral Domain Optical Coherence Tomography Data

Michelle Khan, MD FRCSC**

Lecturer, Ophthalmology & Vision Sciences, University of Toronto

Consultant Ophthalmologist, Trillium Health Partners; Chair, St John of Jerusalem Eye Hospital Group Ophthalmic Association - Canada

The St John Eye Hospital

Rahul G Krishnan, PhD

Assistant Professor, Department of Computer Science and Temerty Faculty of Medicine

Basics of Artificial Intelligence, Machine Learning, and Deep Learning

Muhammad Mamdani, PharmD MA MPH

Vice President - Data Science and Advanced Analytics, Unity Health Toronto; Odette Chair in Advanced Analytics; Faculty Affiliate – Vector Institute; Director - University of Toronto Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM); Professor - University of Toronto

From Compute to Care: Trials and Tribulations of Deploying AI into Clinical Practice

Austin Pereira, MD MEng* (Supervisor: Netan Choudhry, MD FRCSC DABO)

Resident (PGY3), Ophthalmology & Vision Sciences, University of Toronto

Multi-centre validation of a deep learning model to conduct automated segmentation of swept-source optical coherence tomography images for macular hole volume

Marko Popovic, MD* (Supervisor: Matthew Schlenker, MD MSc FRCSC)

Resident (PGY4), Ophthalmology & Vision Sciences, University of Toronto

A Comparison of the Toronto Artificial Intelligence Model for Intraocular Lens Power Calculation to 12 Preoperative Formulas

Laura C Rosella, PhD MHSc

Associate Professor, Dalla Lana School of Public Health, University of Toronto; Education Lead, U of T Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM); Faculty Affiliate, Vector Institute for Artificial Intelligence

AI and Big Data

Matthew Schlenker, MD MSc FRCSC

Associate Professor, Ophthalmology & Vision Sciences, University of Toronto; Clinician Scientist at Institute for Better Health

AI in Eye Surgery: Establishing Surgical Learning Curves

Allan Slomovic, MD MSc FRCSC**

Professor, Vice Chair of Education and Continuing Education Director, Research Director, Cornea Service, University Health Network, Toronto

Q&A Moderator, Concluding Remarks

Andre Stanberry, OD

Clinical Associate Professor and Clinical Director, School of Optometry and Vision Science, University of Waterloo

AI in Optometric Education and Research

Adnan Tufail, MBBS MD FRCOpth

Consultant Ophthalmologist, Moorfields Eye Hospital, London, UK

Current Status of AI in Ophthalmology

David Verity, BMBCh MA(Oxon) MD FRCOpth

Consultant Ophthalmologist, Moorfields Eye Hospital, London, UK Hospitaller, the Most Venerable Order of St John of Jerusalem

Overview of the St John Ophthalmic Association &

Why We Will Always Need Human Intelligence

Alexander Wong, PhD PEng

Professor, Canada Research Chair in AI and Medical Imaging, University of Waterloo

Towards Trustworthy and Transparent Computer Aided Diagnosis for the Eye

David Wong, MD FRCSC

Ophthalmologist-in-Chief, St Michael's Hospital, Toronto

AI and the Retina

**Conference Co-Chair

*Conference Committee