Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Yildirim, Nur; Richardson, Hannah; Teodora Wetscherek, Maria; Bajwa, Junaid; Jacob, Joseph; A. Pinnock, Mark; Harris, Steve; C. Castro, Daniel; Bannur, Shruthi; L. Hyland, Stephanie; Ghosh, Pratik; Ranjit, Mercy; Bouzid, Kenza; Schwaighofer, Anton; Pérez‐García, Fernando; Sharma, Harshita; Oktay, Ozan; P. Lungren, Matthew; Alvarez-Valle, Javier; Nori, Aditya; Thieme, Anja

doi:10.1145/3613904.3642013

Public

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Published • May 11, 2024

Authors:

Nur Yildirim

Hannah Richardson

Maria Teodora Wetscherek

Abstract

Recent advances in AI combine large language models (LLMs) with vision encoders that bring forward unprecedented technical capabilities to leverage for a wide range of healthcare applications. Focusing on the domain of radiology, vision-language models (VLMs) achieve good performance results for tas...

Subject

Leverage (statistics)

Computer science

Multidisciplinary approach

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