Nazli Tokatli
Istanbul Health and Technology University
About the Artificial Intelligence and Deep Learning in Ophthalmology Session
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
Topics Covered in Artificial Intelligence and Deep Learning in Ophthalmology
Topic 01
Diabetic Retinopathy Screening
Topic 02
Convolutional Neural Networks
Topic 03
OCT Image Segmentation
Topic 04
Automated Glaucoma Detection
Topic 05
Explainable AI
Topic 06
Real-World AI Deployment
Featured Speakers — Artificial Intelligence and Deep Learning in Ophthalmology 2027
Recent Research Presented at Artificial Intelligence and Deep Learning in Ophthalmology Sessions
Deep learning-based glaucoma classification from fundus images: Comparative analysis of CNN architectures
Glaucoma represents a leading cause of irreversible blindness worldwide, characterized by progressive optic nerve damage that often progresses asymptomatically until significant vision loss occurs.…
Evaluating the quality and readability of AI generated ophthalmic surgery education: A four model comparison
Background: Artificial Intelligence (AI) tools, particularly Large Language Models (LLMs), are increasingly utilised to provide health information, with patients seeking simplified explanations of…
RetinX an AI powered platform for automated detection and monitoring of ocular and systemic diseases
The rising global burden of vision-threatening conditions highlights the need for scalable, accessible, and accurate screening tools. RetinX is an AI-powered mobile application developed to address…
Evaluating ConvNeXt tiny for multi class diabetic retinopathy detection benchmarking a next generation convolutional architecture against established CNN baselines
Background: Most deep learning systems for Diabetic Retinopathy (DR) screening rely on architectures such as ResNet and EfficientNet, with recent attention shifting towards transformer-based models.…
AI in eye care: Prospects and challenges
Introduction: Artificial Intelligence (AI) has transformed medicine, with various applications across diagnostics and clinical decision tools that have been applied in many specialties, including…
Accuracy of multimodal interpretation by large language models for ophthalmology clinical vignettes
Purpose: Large language models (LLMs) can accept text and image prompts as multimodal input. With implications for ophthalmology as a field, we evaluated the performance of several LLMs on relevant…
Related Scientific Sessions at IOC 2027
Why Attend the Artificial Intelligence and Deep Learning in Ophthalmology Conference 2027
Present Your Research
Oral and poster slots for original Artificial Intelligence and Deep Learning in Ophthalmology work, reviewed by the scientific committee.
Network Globally
Meet ophthalmologists, vision scientists, and eye-care clinicians from around the world across three days.
Publish & Get Indexed
Accepted abstracts are compiled into the conference proceedings and indexed in Scopus and Web of Science.
Learn from Keynotes
Plenary lectures from leading voices shaping Artificial Intelligence and Deep Learning in Ophthalmology research and practice.
Hybrid Flexibility
Attend in person in Singapore or join virtually — same program, same certificate.
Join IOC 2027 for the Artificial Intelligence and Deep Learning in Ophthalmology track
Oral and poster slots for your work — in person in Singapore or online. Not presenting? Attend as a delegate to learn from the field.
Artificial Intelligence and Deep Learning in Ophthalmology Conference 2027 — FAQs
What is the Artificial Intelligence and Deep Learning in Ophthalmology track at IOC 2027?
The Artificial Intelligence and Deep Learning in Ophthalmology track is a dedicated stream within IOC 2027 covering the latest research, clinical innovation, and best practice in Artificial Intelligence and Deep Learning in Ophthalmology. It brings together researchers, educators, and practitioners for oral presentations, posters, and discussion.
Who should attend the Artificial Intelligence and Deep Learning in Ophthalmology sessions?
Ophthalmologists, optometrists, vision scientists, educators, doctoral students, and trainees with an interest in Artificial Intelligence and Deep Learning in Ophthalmology are all welcome — whether presenting or attending.
Can I present my research in the Artificial Intelligence and Deep Learning in Ophthalmology track?
Yes. Submit an abstract for oral or poster presentation. All submissions are peer-reviewed by the scientific committee; accepted abstracts appear in the indexed proceedings.
Is virtual attendance available for Artificial Intelligence and Deep Learning in Ophthalmology sessions?
Yes. IOC 2027 is a hybrid conference — attend the Artificial Intelligence and Deep Learning in Ophthalmology track in person in Singapore or join live online, with on-demand access afterward.
Join the IOC 2027 delegation
Singapore · March 15–17, 2027· Hybrid · in-person & virtual
Register as Delegate →
Attend without presenting.