Uploaded January 2026 | Updated September 2026, 2 weeks ago
In this video, Pearse Keane and Yukun Zhou (UCL) presents 'Foundation Models in Healthcare - Reinventing the Eye Exam'.
Presentation Date: 12/06/23
Abstract: Ophthalmology is among the most technology-driven of the all the medical specialties, with treatments utilizing high-spec medical lasers and advanced microsurgical techniques, and diagnostics involving ultra-high resolution imaging. Ophthalmology is also at the forefront of many trailblazing research areas in healthcare, such as stem cell therapy, gene therapy, and - most recently - artificial intelligence. In our presentation, we will describe the development of RETFound, a foundation model for ophthalmology. RETFound was trained on 1.6 million retinal images using self-supervised learning and utilising a vision transformer architecture. In a recent publication in Nature, we demonstrate that RETFound performs better that other approaches for a diverse range of downstream clinical tasks, from diabetic retinopathy screening to predicting progression of age-related macular degeneration, to using the eye as a window to systemic disease (“oculomics”). We also show that RETFound is more robust on external validation, fairer across ethnicities, and more label efficient, opening the possibility of its use in less common retinal disease. We will describe the process to create this foundation model as well as our plans to scale and validate the model, going from nearly 2 million to 20 million images, and making it both 3D and truly multi-modal.
Bio: Pearse Keane is Professor of Artificial Medical Intelligence at UCL Institute of Ophthalmology, and a consultant ophthalmologist at Moorfields Eye Hospital, London. Since 2020, he has been funded by UK Research & Innovation (UKRI) as a Future Leaders Fellow, and in 2023 he became a National Institute for Health Research (NIHR) Senior Investigator. He is originally from Ireland and received his medical degree from University College Dublin (UCD), graduating in 2002. In 2016, he initiated a collaboration between Moorfields Eye Hospital and Google DeepMind, with the aim of developing artificial intelligence (AI) algorithms for the earlier detection and treatment of retinal disease. In August 2018, the first results of this collaboration were published in the journal, Nature Medicine. In May 2020, he jointly led work, again published in Nature Medicine, to develop an early warning system for age-related macular degeneration (AMD), by far the commonest cause of blindness in many countries. In 2023, he led the development of RETFound, the first foundation model in ophthalmology, published in Nature and made available open source. In October 2019, he was included on the Evening Standard Progress1000 list of most influential Londoners (standard.co.uk/news/the1000) and in June 2020, he was profiled in The Economist (economist.com/technology-quarterly/2020/06/11/the-potential-and-the-pitfalls-of-medical-ai). In 2022, he was listed in the “Top10” of the “The Power List” by The Ophthalmologist magazine, a ranking of the Top 100 most influential people in the world of ophthalmology (theophthalmologist.com/power-list/2022).
Yukun Zhou is a final-year PhD student working at UCL Centre for Medical Image Computing and Moorfields Eye Hospital Biomedical Research Centre. He mainly works on retinal image analysis and translation research on large-scale clinical data in Ophthalmology. In 2022, he released ""AutoMorph"", the first open-source fully automated analysis tool in the retinal image analysis. Related applications have been published in journals such as Jama Psychiatry and Cell Metabolism. In 2023, he published the open-source research ""RETFound"" in Nature, the first foundation model in ophthalmology. He received UCL’s inaugural Open Science and Scholarship Award.
For more information, visit: broadinstitute.org/ml4h
Copyright Broad Institute, 2025. All rights reserved.
In this video, Pearse Keane and Yukun Zhou (UCL) presents 'Foundation Models in Healthcare - Reinventing the Eye Exam'.
Presentation Date: 12/06/23
Abstract: Ophthalmology is among the most technology-driven of the all the medical specialties, with treatments utilizing high-spec medical lasers and advanced microsurgical techniques, and diagnostics involving ultra-high resolution imaging. Ophthalmology is also at the forefront of many trailblazing research areas in healthcare, such as stem cell therapy, gene therapy, and - most recently - artificial intelligence. In our presentation, we will describe the development of RETFound, a foundation model for ophthalmology. RETFound was trained on 1.6 million retinal images using self-supervised learning and utilising a vision transformer architecture. In a recent publication in Nature, we demonstrate that RETFound performs better that other approaches for a diverse range of downstream clinical tasks, from diabetic retinopathy screening to predicting progression of age-related macular degeneration, to using the eye as a window to systemic disease (“oculomics”). We also show that RETFound is more robust on external validation, fairer across ethnicities, and more label efficient, opening the possibility of its use in less common retinal disease. We will describe the process to create this foundation model as well as our plans to scale and validate the model, going from nearly 2 million to 20 million images, and making it both 3D and truly multi-modal.
Bio: Pearse Keane is Professor of Artificial Medical Intelligence at UCL Institute of Ophthalmology, and a consultant ophthalmologist at Moorfields Eye Hospital, London. Since 2020, he has been funded by UK Research & Innovation (UKRI) as a Future Leaders Fellow, and in 2023 he became a National Institute for Health Research (NIHR) Senior Investigator. He is originally from Ireland and received his medical degree from University College Dublin (UCD), graduating in 2002. In 2016, he initiated a collaboration between Moorfields Eye Hospital and Google DeepMind, with the aim of developing artificial intelligence (AI) algorithms for the earlier detection and treatment of retinal disease. In August 2018, the first results of this collaboration were published in the journal, Nature Medicine. In May 2020, he jointly led work, again published in Nature Medicine, to develop an early warning system for age-related macular degeneration (AMD), by far the commonest cause of blindness in many countries. In 2023, he led the development of RETFound, the first foundation model in ophthalmology, published in Nature and made available open source. In October 2019, he was included on the Evening Standard Progress1000 list of most influential Londoners (standard.co.uk/news/the1000) and in June 2020, he was profiled in The Economist (economist.com/technology-quarterly/2020/06/11/the-potential-and-the-pitfalls-of-medical-ai). In 2022, he was listed in the “Top10” of the “The Power List” by The Ophthalmologist magazine, a ranking of the Top 100 most influential people in the world of ophthalmology (theophthalmologist.com/power-list/2022).
Yukun Zhou is a final-year PhD student working at UCL Centre for Medical Image Computing and Moorfields Eye Hospital Biomedical Research Centre. He mainly works on retinal image analysis and translation research on large-scale clinical data in Ophthalmology. In 2022, he released ""AutoMorph"", the first open-source fully automated analysis tool in the retinal image analysis. Related applications have been published in journals such as Jama Psychiatry and Cell Metabolism. In 2023, he published the open-source research ""RETFound"" in Nature, the first foundation model in ophthalmology. He received UCL’s inaugural Open Science and Scholarship Award.
For more information, visit: broadinstitute.org/ml4h
Copyright Broad Institute, 2025. All rights reserved.
