1.3k citations · 3.7k across the 23 of their papers we have counts for
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A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges
Zifeng Wang, Hanyin Wang, Benjamin Danek +6
The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to cli…
ReXplain: Translating Radiology into Patient-Friendly Video Reports
Luyang Luo, Jenanan Vairavamurthy, Xiaoman Zhang +7
Radiology reports, designed for efficient communication between medical experts, often remain incomprehensible to patients. This inaccessibility could potentially lead to anxiety,…
ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics
Oishi Banerjee, Agustina Saenz, Kay Wu +17
Given the rapidly expanding capabilities of generative AI models for radiology, there is a need for robust metrics that can accurately measure the quality of AI-generated radiology…
A Large Model for Non-invasive and Personalized Management of Breast Cancer from Multiparametric MRI
Luyang Luo, Mingxiang Wu, Mei Li +8
Breast Magnetic Resonance Imaging (MRI) demonstrates the highest sensitivity for breast cancer detection among imaging modalities and is standard practice for high-risk women. Inte…
Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining
Sameer Khanna, Daniel Michael, Marinka Zitnik +1
Medical image interpretation using deep learning has shown promise but often requires extensive expert-annotated datasets. To reduce this annotation burden, we develop an Image-Gra…
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores
Alyssa Huang, Oishi Banerjee, Kay Wu +2
The current gold standard for evaluating generated chest x-ray (CXR) reports is through radiologist annotations. However, this process can be extremely time-consuming and costly, e…
GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration
Sunan He, Yuxiang Nie, Hongmei Wang +21
Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…