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4th Edition of
International Ophthalmology Conference
March 23-25, 2026 | Singapore
Artificial Intelligence and Deep Learning in Ophthalmology
Artificial Intelligence and Deep Learning in Ophthalmology
The fourth industrial revolution in human history is artificial intelligence (AI). Deep learning (DL) is a class of cutting-edge machine learning algorithms that has aroused a lot of attention throughout the world in recent years. DL is a revolutionary AI machine learning technology that has completely transformed the AI sector. DL has demonstrated clinically acceptable diagnostic performance in detecting several retinal disorders in ophthalmology. Future study will be necessary to assess the clinical deployment and cost-effectiveness of various DL systems in clinical practise. To increase clinical acceptance of DL systems, present and future approaches must be used to unravel the ‘black-box' aspect of DL.
- Fundus Photographs
- Optical Coherence
- Tomography and Visual Field
- Ocular Imaging
- AI 'Black-Box' Algorithms
- Telemedicine
Committee Members
Shadrokh Nabili
University Hospitals of Morecambe Bay NHS Foundation Trust, United Kingdom
Anna Maria Bassi
University of Genoa, Italy
Tim Jackson
King’s College London, United Kingdom IOC 2026 Speakers
Pio Conti
University of Chieti, Italy
Gowhar Ahmad
Florence Hospital Srinagar, India
Agnieszka Rosa
Orticus Center for the Treatment of Strabismus and Vision Disorders, Poland
Arrane Selvamogan
Leicestershire Partnership NHS Trust, United KingdomSubmit your abstract Today
Title : Rare and interesting case of Goldenhar’s syndrome in a 3 years old male child
Gowhar Ahmad, Florence Hospital Srinagar, India
Title : Management of common vitreoretinal lesions: An overview and update
Tim Jackson, King’s College London, United Kingdom
Title : Lumevoq gene therapy in leber hereditary optic neuropathy
Magali Taiel, GenSight Biologics, France
Title : An advanced 3D human-based in vitro model to identify disease-specific molecular markers of glaucoma neurodegeneration
Anna Maria Bassi, University of Genoa, Italy
Title : Evaluating the quality and readability of AI chatbot responses to frequently asked questions on basal cell carcinoma: Implications for patient education and digital health communication
Arrane Selvamogan, Leicestershire Partnership NHS Trust, United Kingdom
Title : Evaluating the quality and readability of AI-generated ophthalmic surgery education: A four-model comparison
Arrane Selvamogan, Leicestershire Partnership NHS Trust, United Kingdom