Identifying cases of metastatic prostate cancer using machine learning on electronic health records. - Martin G. Seneviratne; Juan M. Banda; James D. Brooks; Nigam Shah; Tina Hernandez-Boussard (AMIA, 2018)

Machine Learning Approaches for Extracting Stage from Pathology Reports in Prostate Cancer. - Raphael Lenain; Martin G. Seneviratne; Selen Bozkurt; Douglas W. Blayney; James D. Brooks; Tina Hernandez-Boussard (MedInfo, 2019)

Merging heterogeneous clinical data to enable knowledge discovery. - Martin G. Seneviratne; Michael G. Kahn; Tina Hernandez-Boussard (PSB, 2019)

Learning to Select Best Forecast Tasks for Clinical Outcome Prediction. - Yuan Xue; Nan Du 002; Anne Mottram; Martin Seneviratne; Andrew M. Dai (NeurIPS, 2020)

Reporting of demographic data and representativeness in machine learning models using electronic health records. - Selen Bozkurt; Eli M. Cahan; Martin G. Seneviratne; Ran Sun; Juan Antonio Lossio-Ventura; John P. A. Ioannidis; Tina Hernandez-Boussard (J. Am. Medical Informatics Assoc., 2020)

Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network. - Mehr Kashyap; Martin G. Seneviratne; Juan M. Banda; Thomas Falconer; Borim Ryu; Sooyoung Yoo; George Hripcsak; Nigam H. Shah (J. Am. Medical Informatics Assoc., 2020)

Concept-based model explanations for electronic health records. - Diana Mincu; Eric Loreaux; Shaobo Hou; Sebastien Baur; Ivan Protsyuk; Martin Seneviratne; Anne Mottram; Nenad Tomasev; Alan Karthikesalingam; Jessica Schrouff (CHIL, 2021)

BEDS-Bench: Behavior of EHR-models under Distributional Shift-A Benchmark. - Anand Avati; Martin Seneviratne; Emily Xue; Zhen Xu 006; Balaji Lakshminarayanan; Andrew M. Dai (CoRR, 2021)

Multitask prediction of organ dysfunction in the intensive care unit using sequential subnetwork routing. - Subhrajit Roy; Diana Mincu; Eric Loreaux; Anne Mottram; Ivan Protsyuk; Natalie Harris; Yuan Xue; Jessica Schrouff; Hugh Montgomery; Alistair Connell; Nenad Tomasev; Alan Karthikesalingam; et al. (J. Am. Medical Informatics Assoc., 2021)

Instability in clinical risk stratification models using deep learning. - Daniel Lopez Martinez; Alex Yakubovich; Martin Seneviratne; Ádám D. Lelkes; Akshit Tyagi; Jonas Kemp; Ethan Steinberg; N. Lance Downing; Ron C. Li; Keith E. Morse; Nigam H. Shah; Ming-Jun Chen (ML4H@NeurIPS, 2022)

Automated LOINC Standardization Using Pre-trained Large Language Models. - Tao Tu 001; Eric Loreaux; Emma Chesley; Ádám D. Lelkes; Paul Gamble; Mathias Bellaiche; Martin Seneviratne; Ming-Jun Chen (ML4H@NeurIPS, 2022)

Walking with PACE - Personalized and Automated Coaching Engine. - Madhurima Vardhan; Narayan Hegde; Srujana Merugu; Shantanu Prabhat; Deepak Nathani; Martin Seneviratne; Nur Muhammad; Pranay Reddy; Sriram Lakshminarasimhan; Rahul Singh; Karina Lorenzana; Eshan Motwani; et al. (UMAP, 2022)

Boosting the interpretability of clinical risk scores with intervention predictions. - Eric Loreaux; Ke Yu; Jonas Kemp; Martin Seneviratne; Christina Chen; Subhrajit Roy; Ivan Protsyuk; Natalie Harris; Alexander D'Amour; Steve Yadlowsky; Mingjun Chen (CoRR, 2022)

Large Language Models Encode Clinical Knowledge. - Karan Singhal; Shekoofeh Azizi; Tao Tu 001; S. Sara Mahdavi; Jason Wei; Hyung Won Chung; Nathan Scales; Ajay Kumar Tanwani; Heather Cole-Lewis; Stephen Pfohl; Perry Payne; Martin Seneviratne; et al. (CoRR, 2022)

Expanding the Secondary Use of Prostate Cancer Real World Data: Automated Classifiers for Clinical and Pathological Stage. - Selen Bozkurt; Christopher J. Magnani; Martin G. Seneviratne; James D. Brooks; Tina Hernandez-Boussard (Frontiers Digit. Health, 2022)

Underspecification Presents Challenges for Credibility in Modern Machine Learning. - Alexander D'Amour; Katherine A. Heller; Dan Moldovan; Ben Adlam; Babak Alipanahi; Alex Beutel; Christina Chen; Jonathan Deaton; Jacob Eisenstein; Matthew D. Hoffman; Farhad Hormozdiari; Neil Houlsby; et al. (J. Mach. Learn. Res., 2022)

Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction. - Yuan Xue; Nan Du 002; Anne Mottram; Martin Seneviratne; Andrew M. Dai (CoRR, 2024)