Tracing the history of artificial intelligence (AI) in ophthalmology through to the latest work on foundation models, INSIGHT director Pearse Keane recently presented to the Broad Institute’s Machine Learning for Health (ML4H) initiative, together with Yukun Zhou, research fellow at University College London and Moorfields Eye Hospital.
Speaking at the ML4H seminar, Pearse addressed the challenges of translation and progress to date, while Yukun explained how the world’s first foundation model in ophthalmology was developed, outlining why the open-source model is an important step forward for research into disease that is detectable through retinal scans.
ML4H is an effort led by the Broad Institute in collaboration with faculty members from Massachusetts General Hospital, Brigham and Women’s Hospital, and MIT. The goal is to use machine learning to drive new fundamental research into disease and risk prediction.
Based in Cambridge, Massachusetts, the Broad Institute was founded in 2004 to fulfill the promise of genomic medicine—three years after completion of the Human Genome Project, which Broad scientists helped create and lead.
Watch the seminar recording below (courtesy of ML4H).
For more information on the Broad Institute’s ML4H and how to get involved: https://www.broadinstitute.org/ml4h
About Pearse Keane
Pearse is Professor of Artificial Medical Intelligence at University College London’s Institute of Ophthalmology, a consultant ophthalmologist at Moorfields Eye Hospital NHS Foundation Trust, and director of the INSIGHT Health Data Research Hub Programme, the world’s largest bioresource of ophthalmic images linked to clinical data.
About Yukun Zhou
Yukun is a research fellow at University College London and Moorfields Eye Hospital. His work focuses on generalisable retinal image analysis and large-scale translational research.
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