335 citations · 389 across the 9 of their papers we have counts for
9 papers
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…
MINT: A wrapper to make multi-modal and multi-image AI models interactive
Jan Freyberg, Abhijit Guha Roy, Terry Spitz +10
During the diagnostic process, doctors incorporate multimodal information including imaging and the medical history - and similarly medical AI development has increasingly become m…
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…
Masked Diffusion with Task-awareness for Procedure Planning in Instructional Videos
Fen Fang, Yun Liu, Ali Koksal +2
A key challenge with procedure planning in instructional videos lies in how to handle a large decision space consisting of a multitude of action types that belong to various tasks.…
ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders
Shawn Xu, Lin Yang, Christopher Kelly +25
In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder combined or grafted onto…
Towards Generalist Biomedical AI
Tao Tu, Shekoofeh Azizi, Danny Driess +29
Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly en…