Supervised Transfer Learning at Scale for Medical Imaging. - Basil Mustafa; Aaron Loh; Jan Freyberg; Patricia MacWilliams; Megan Wilson; Scott Mayer McKinney; Marcin Sieniek; Jim Winkens; Yuan Liu; Peggy Bui; Shruthi Prabhakara; Umesh Telang; et al. (CoRR, 2021)

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)

AI system for fetal ultrasound in low-resource settings. - Ryan G. Gomes; Bellington Vwalika; Chace Lee; Angelica Willis; Marcin Sieniek; Joan T. Price; Christina Chen; Margaret P. Kasaro; James A. Taylor 003; Elizabeth M. Stringer; Scott Mayer McKinney; Ntazana Sindano; et al. (CoRR, 2022)

Robust and Efficient Medical Imaging with Self-Supervision. - Shekoofeh Azizi; Laura Culp; Jan Freyberg; Basil Mustafa; Sebastien Baur; Simon Kornblith; Ting Chen 007; Patricia MacWilliams; S. Sara Mahdavi; Ellery Wulczyn; Boris Babenko; Megan Wilson; et al. (CoRR, 2022)

Capabilities of GPT-4 on Medical Challenge Problems. - Harsha Nori; Nicholas King; Scott Mayer McKinney; Dean Carignan; Eric Horvitz (CoRR, 2023)

Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. - Harsha Nori; Yin Tat Lee; Sheng Zhang 012; Dean Carignan; Richard Edgar; Nicolò Fusi; Nicholas King; Jonathan Larson; Yuanzhi Li; Weishung Liu; Renqian Luo; Scott Mayer McKinney; et al. (CoRR, 2023)

From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond. - Harsha Nori; Naoto Usuyama; Nicholas King; Scott Mayer McKinney; Xavier Fernandes; Sheng Zhang 012; Eric Horvitz (CoRR, 2024)