activity
20152025
most citedPredicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning

1.9k citations · 5.7k across the 29 of their papers we have counts for

collaborators

29 papers

cs.CL2025★ 1 cited

LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load

Theo Guidroz, Diego Ardila, Jimmy Li +24

Information on the web, such as scientific publications and Wikipedia, often surpasses users' reading level. To help address this, we used a self-refinement approach to develop a L…

cs.CV2025★ 1 cited

PolyPath: Adapting a Large Multimodal Model for Multi-slide Pathology Report Generation

Faruk Ahmed, Lin Yang, Tiam Jaroensri +11

The interpretation of histopathology cases underlies many important diagnostic and treatment decisions in medicine. Notably, this process typically requires pathologists to integra…

cs.CV2024★ 2 cited

PathAlign: A vision-language model for whole slide images in histopathology

Faruk Ahmed, Andrew Sellergren, Lin Yang +14

Microscopic interpretation of histopathology images underlies many important diagnostic and treatment decisions. While advances in vision-language modeling raise new opportunities…

cs.AI2024★ 96 cited

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…

cs.CY2024★ 22 cited

Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset

Abbi Ward, Jimmy Li, Julie Wang +17

Background: Health datasets from clinical sources do not reflect the breadth and diversity of disease in the real world, impacting research, medical education, and artificial intel…

eess.IV2024

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong +23

Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little i…