Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning. - Gabriel G. Erion; Hugh Chen; Scott M. Lundberg; Su-In Lee (CoRR, 2017)

Consistent Individualized Feature Attribution for Tree Ensembles. - Scott M. Lundberg; Gabriel G. Erion; Su-In Lee (CoRR, 2018)

Explainable AI for Trees: From Local Explanations to Global Understanding. - Scott M. Lundberg; Gabriel G. Erion; Hugh Chen; Alex J. DeGrave; Jordan M. Prutkin; Bala Nair; Ronit Katz; Jonathan Himmelfarb; Nisha Bansal; Su-In Lee (CoRR, 2019)

Learning Explainable Models Using Attribution Priors. - Gabriel G. Erion; Joseph D. Janizek; Pascal Sturmfels; Scott M. Lundberg; Su-In Lee (CoRR, 2019)

An adversarial approach for the robust classification of pneumonia from chest radiographs. - Joseph D. Janizek; Gabriel G. Erion; Alex J. DeGrave; Su-In Lee (CHIL, 2020)

Deep Transfer Learning for Physiological Signals. - Hugh Chen; Scott M. Lundberg; Gabriel G. Erion; Jerry H. Kim; Su-In Lee (CoRR, 2020)

From local explanations to global understanding with explainable AI for trees. - Scott M. Lundberg; Gabriel G. Erion; Hugh Chen; Alex J. DeGrave; Jordan M. Prutkin; Bala Nair; Ronit Katz; Jonathan Himmelfarb; Nisha Bansal; Su-In Lee (Nat. Mach. Intell., 2020)

Improving performance of deep learning models with axiomatic attribution priors and expected gradients. - Gabriel G. Erion; Joseph D. Janizek; Pascal Sturmfels; Scott M. Lundberg; Su-In Lee (Nat. Mach. Intell., 2021)

Forecasting adverse surgical events using self-supervised transfer learning for physiological signals. - Hugh Chen; Scott M. Lundberg; Gabriel G. Erion; Jerry H. Kim; Su-In Lee (npj Digit. Medicine, 2021)

New AI Frameworks for Real-World Clinical Prediction. - Gabriel G. Erion (2021)