2022 Agenda
8:00 AM – New York/Eastern Time Zone
Session 1
8:00 AM Addressing AI Bias in Retinal Diagnostics
Neil Bressler, MD
8:10 AM Fluctuations in fluid volume portend worse visual acuity outcomes
Usha Chakravarthy, MD, PhD, CBE
8:20 AM Validation of an AI-based algorithm for quantification of fluid nAMD
Judy Kim, MD
8:30 AM Exploratory analysis of Faricimab treatment response using machine learning
Jian Dai, PhD
8:40 AM Retinal layer disruption on OCT in neovascular age-related macular degeneration Segmented by Deep Learning
Yvonna Li, MSc1
8:50 AM Machine learning to predict fibrosis development in neovascular age-related macular degeneration
Andreas Maunz, PhD
9:00 AM Panel Discussion: All Session 1 Faculty
Session 2
9:15 AM Machine learning quantification of fluid volume in eyes with neovascular ARMD and retinal vein occlusion: the ONTARIO & Revolt studies
Netan Choudhry, MD, FRCSC, DABO
9:25 AM AI algorithms for AMD as informed by the AREDS and AREDS2 Studies
Emily Chew, MD
9:35 AM Tracking disease dynamics and treatment response with AI-enabled home OCT
Jeffrey S. Heier, MD
9:45 AM Emerging applications of artificial intelligence in the analysis of biofluid markers involved in retinal occlusive diseases: A systematic review
Daiana Roxana Pur, MESc
9:55 AM Identifying non-responders post aflibercept loading phase for neovascular AMD using artificial intelligence
Sobha Sivaprasad, MS Ophth, DNB, DM, FRCS(Ed), FRCOphth
10:05 AM AI-based fluid quantification in PCV
Gemmy Chung, MBBS, FRCOphth, FAMS, MCI
10:15 AM Panel Discussion: All Session 2 Faculty
10:30 AM Break and sponsor presentation
Session 3
10:40 AM Geographic atrophy (GA): Identification of disease activity and therapeutic response by AI tools
Ursula Schmidt-Erfurth, MD
10:50 AM Prognostic models in Geographic Atrophy: development and validation
Neha Anegondi
11:00 AM Deep learning-based ablation studies for feature discovery in geographic atrophy progression
Daniela Ferrara, MD, MSc, PhD
11:10 AM Utilizing machine learning for automated segmentation of geographic atrophy lesions on spectral domain optical coherence tomography
Gagan Kalra, MD
11:20 AM Ophthalmic AI… why is it far ahead of other healthcare AI applications?
Frank Cheng, MBA
11:30 AM Fiven(5) rights of AI in Ophthalmology
Daniel Ting, MBBS (Hons), BSciMed, FRCOphth, MMed (Ophth), FAMS, PhD
11:40 AM Panel Discussion: All Session 3 Faculty
Session 4
11:55 AM A practical guide to pitfalls in the applications of machine learning in medical imaging
Jayashree Kalpathy-Cramer, PhD
12:05 PM How can we support AI research? The National Eye Institute perspective
Michael F. Chiang, MD
12:15 PM The AI bias: How do we set performance expectations
Luis de Sisternes, PhD
12:25 PM The adoption of rigorously validated AI to enhance access for patients from point-of-care to specialist care
Michael D. Abràmoff, MD, PhD
12:35 PM The Moorfields-DeepMind collaboration – Going from Code to Clinic
Pearse A. Keane MD, FRCOphth
12:45 PM Clinician-driven AI: resources enabling democratization
Edward Korot, MD
12:55 PM Panel Discussion: All Session 4 Faculty
1:10 PM Break
Session 5
1:20 PM The application of artificial intelligence in the analysis of biomarkers for diagnosis and management of uveal diseases: A systematic review
Arshpreet Bassi
1:30 PM Applications of AI in retinopathy of prematurity
J. Peter Campbell, MD, MPH
1:40 PM Doing more with less – A contrastive learning pipeline for robust diabetic retinopathy classification
Minhaj Nur Alam,PhD
1:50 PM Incorporating AI into a diabetic retinopathy screening workflow in an academic primary health care network
David Myung, MD, PhD
2:00 PM Predicting progression in diabetic retinopathy: clinical application of OCTA and federated learning algorithms
Amani Fawzi, MD
2:10 PM Eye-net: A novel machine learning ensemble for the efficient, interpretable diagnosis and localization of lesions in diabetic retinopathy
Justin Liu
2:20 PM Automated Classification of Diabetic Retinopathy Severity Score for Clinical Trial Eligibility
Amitha Domalpally, MD, PhD
2:30 PM Panel Discussion: All Session 5 Faculty
Session 6
2:45 PM Machine learning for differential artery-vein analysis in OCT and OCTA
David Le, PhD
2:55 PM Moderately severe and severe nonproliferative diabetic retinopathy identified by deep learning
Fethallah Benmansour, PhD
3:05 PM Automated etiologic classification of macular edema in Optical Coherence Tomography scans
Fabio Daniel Padilla, MD
3:15 PM Predictors for non-diagnostic images in real world deployment of artificial intelligence assisted diabetic retinopathy screening
T.Y. Alvin Liu, MD
3:25 PM Predicting outcomes and treatment frequency following monthly aflibercept for macular edema secondary to central retinal vein occlusion: a machine learning model approach
Yasha Modi, MD
3:35 PM The role of artificial intelligence in analysis of fluid biomarkers for diagnosis and management of glaucoma: a systematic review
Aidan Pucchio
3:45 PM AI and predictive modeling of glaucoma progression using EHR data from the NIH All of Us Research Program
Sally L. Baxter, MD, MSc
3:55 PM A Photographic ROP Severity Score for Treatment Decision Making: Description, Comparison, and Validation
Darius Moshfeghi, MD
4:05 PM Panel Discussion: All Session 6 Faculty
4:20 PM Meeting Adjourns