Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases. - Zaid Nabulsi; Andrew Sellergren; Shahar Jamshy; Charles Lau; Eddie Santos; Atilla P. Kiraly; Wenxing Ye; Jie Yang; Sahar Kazemzadeh; Jin Yu; Raju Kalidindi; Mozziyar Etemadi; et al. (CoRR, 2020)

Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries. - Sahar Kazemzadeh; Jin Yu; Shahar Jamshy; Rory Pilgrim; Zaid Nabulsi; Christina Chen; Neeral Beladia; Charles Lau; Scott Mayer McKinney; Thad Hughes; Atilla P. Kiraly; Sreenivasa Raju Kalidindi; et al. (CoRR, 2021)

Multimodal LLMs for Health Grounded in Individual-Specific Data. - Anastasiya Belyaeva; Justin Cosentino; Farhad Hormozdiari; Krish Eswaran; Shravya Shetty; Greg Corrado; Andrew Carroll; Cory Y. McLean; Nicholas A. Furlotte (ML4MHD, 2023)

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; Marcin Sieniek; Timo Kohlberger; Martin Ma; Wei-Hung Weng; Attila Kiraly; Sahar Kazemzadeh; Zakkai Melamed; Jungyeon Park; Patricia Strachan; et al. (CoRR, 2023)

General Geospatial Inference with a Population Dynamics Foundation Model. - Mohit Agarwal; Mimi Sun; Chaitanya Kamath; Arbaaz Muslim; Prithul Sarker; Joydeep Paul; Hector Yee; Marcin Sieniek; Kim Philipp Jablonski; Yael Mayer; David Fork; Sheila de Guia; et al. (CoRR, 2024)