576 citations · 879 across the 7 of their papers we have counts for
7 papers
Capabilities of Gemini Models in Medicine
Khaled Saab, Tao Tu, Wei-Hung Weng +64
Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of…
Domain-specific optimization and diverse evaluation of self-supervised models for histopathology
Jeremy Lai, Faruk Ahmed, Supriya Vijay +13
Task-specific deep learning models in histopathology offer promising opportunities for improving diagnosis, clinical research, and precision medicine. However, development of such…
Discovering novel systemic biomarkers in photos of the external eye
Boris Babenko, Ilana Traynis, Christina Chen +16
External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about…
Improving Medical Annotation Quality to Decrease Labeling Burden Using Stratified Noisy Cross-Validation
Joy Hsu, Sonia Phene, Akinori Mitani +4
As machine learning has become increasingly applied to medical imaging data, noise in training labels has emerged as an important challenge. Variability in diagnosis of medical ima…
Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photos
Sonia Phene, R. Carter Dunn, Naama Hammel +17
Glaucoma is the leading cause of preventable, irreversible blindness world-wide. The disease can remain asymptomatic until severe, and an estimated 50%-90% of people with glaucoma…
Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program
Paisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse +29
Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical…