Moderators: Mingguang HE & Paisan RUAMVIBOONSUK
| TIME | TITLE | PRESENTER |
| 15:00-15:09 | 3D Convolutional Neural Network (CNN) based abnormality classification in Optical Coherence Tomography (OCT) images | Krunalkumar PATEL |
| 15:09-15:18 | Development & Validation of an Offline Deep Learning Algorithm for Detecting Vitreoretinal Abnormalities on Ocular Ultrasound | Krishna VENKTAESH |
| 15:18-15:27 | Capsule Network Based Classification of Age-Related Macular Disease Using Optical Coherence Tomography Images | Ali CELEBI |
| 15:27-15:36 | The Diagnostic Accuracy of an Artificial Intelligence Tool for Diabetic Retinopathy Using Nonmydriatic Fundus Images | Ganesh JONNADULA |
| 15:36-15:45 | COVID-19 Lockdown: Not a Barrier for Retinopathy of Prematurity Screening | Ashwin SEGI |
| 15:45-15:54 | Anterior Segment Imaging Using a Simple Universal Smartphone Attachment for Patients | Vineet JOSHI |
| 15:54-16:03 | Assessment of Referable Diabetic Retinopathy by Tele-ophthalmology Versus Fundus Examination by Retina Specialist in Diabetes Care Clinics in India | Ramachandran RAJALAKSHMI |
| 16:03-16:12 | Agreement and Diagnostic Test Accuracy of Diabetic Retinopathy Grading Using Fundus Photographs as Compared to Indirect Ophthalmoscopy at a Primary Eye Care Setting in Nepal: The Bhaktapur Retina Study | Raba THAPA |
| 16:12-16:21 | Comparative Assessment of Tear Function Tests, Tear Osmolarity, and Conjunctival Impression Cytology between Patients with Pterygium and Healthy Eyes | Nader NASSIRI |
| 16:21-16:30 | Evaluation of SARS-COV2 Virus via Tears and Conjunctival Secretions of COVID-19 Patients and its Effectiveness as Diagnostic Tool | Ambreen GUL |
