Using Ontologies To Improve Performance In Massively Multi-label Prediction Models. - Ethan Steinberg; Peter J. Liu (CoRR, 2019)

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (CoRR, 2020)

Trove: Ontology-driven weak supervision for medical entity classification. - Jason A. Fries; Ethan Steinberg; Saelig Khattar; Scott L. Fleming; José D. Posada; Alison Callahan; Nigam H. Shah (CoRR, 2020)

Estimating the efficacy of symptom-based screening for COVID-19. - Alison Callahan; Ethan Steinberg; Jason A. Fries; Saurabh Gombar; Birju S. Patel; Conor K. Corbin; Nigam H. Shah (npj Digit. Medicine, 2020)

Computational drug repositioning of atorvastatin for ulcerative colitis. - Lawrence Bai; Madeleine K. D. Scott; Ethan Steinberg; Laurynas Kalesinskas; Aida Habtezion; Nigam H. Shah; Purvesh Khatri (J. Am. Medical Informatics Assoc., 2021)

Learning decision thresholds for risk stratification models from aggregate clinician behavior. - Birju S. Patel; Ethan Steinberg; Stephen R. Pfohl; Nigam H. Shah (J. Am. Medical Informatics Assoc., 2021)

Language models are an effective representation learning technique for electronic health record data. - Ethan Steinberg; Kenneth Jung; Jason A. Fries; Conor K. Corbin; Stephen R. Pfohl; Nigam H. Shah (J. Biomed. Informatics, 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)

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Curtis P. Langlotz; Matthew P. Lungren; Serena Yeung; Nigam Shah; Jason Alan Fries (NeurIPS, 2023)

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models. - Michael Wornow; Rahul Thapa; Ethan Steinberg; Jason A. Fries; Nigam Shah (NeurIPS, 2023)

Self-Supervised Time-to-Event Modeling with Structured Medical Records. - Ethan Steinberg; Yizhe Xu; Jason A. Fries; Nigam Shah (CoRR, 2023)

The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs. - Michael Wornow; Yizhe Xu; Rahul Thapa; Birju S. Patel; Ethan Steinberg; Scott L. Fleming; Michael A. Pfeffer; Jason A. Fries; Nigam H. Shah (CoRR, 2023)

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Matthew P. Lungren; Curtis P. Langlotz; Serena Yeung; Nigam H. Shah; Jason A. Fries (CoRR, 2023)

The shaky foundations of large language models and foundation models for electronic health records. - Michael Wornow; Yizhe Xu; Rahul Thapa; Birju S. Patel; Ethan Steinberg; Scott L. Fleming; Michael A. Pfeffer; Jason Alan Fries; Nigam H. Shah (npj Digit. Medicine, 2023)

The Prevalence of Confidential Content in Adolescent Progress Notes Prior to the 21st Century Cures Act Information Blocking Mandate. - Michael Bedgood; Naveed Rabbani; Conner Brown; Rachel L. Goldstein; Jennifer L. Carlson; Ethan Steinberg; Austin Powell; Natalie M. Pageler; Keith E. Morse (Appl. Clin. Inform., 2023)

Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease. - Yizhe Xu; Agata Foryciarz; Ethan Steinberg; Nigam H. Shah (J. Am. Medical Informatics Assoc., 2023)

A Natural Language Processing Model to Identify Confidential Content in Adolescent Clinical Notes. - Naveed Rabbani; Michael Bedgood; Conner Brown; Ethan Steinberg; Rachel L. Goldstein; Jennifer L. Carlson; Natalie M. Pageler; Keith E. Morse (Appl. Clin. Inform., 2023)

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks. - Joshua Lemmon; Lin Lawrence Guo; Ethan Steinberg; Keith E. Morse; Scott Lanyon Fleming; Catherine Aftandilian; Stephen R. Pfohl; José D. Posada; Nigam Shah; Jason Alan Fries; Lillian Sung (J. Am. Medical Informatics Assoc., 2023)

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. - Scott L. Fleming; Alejandro Lozano; William J. Haberkorn; Jenelle A. Jindal; Eduardo Pontes Reis; Rahul Thapa; Louis Blankemeier; Julian Z. Genkins; Ethan Steinberg; Ashwin Nayak 002; Birju S. Patel; Chia-Chun Chiang; et al. (AAAI, 2024)

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records. - Ethan Steinberg; Jason Alan Fries; Yizhe Xu; Nigam Shah (ICLR, 2024)

meds_reader: A fast and efficient EHR processing library. - Ethan Steinberg; Michael Wornow; Suhana Bedi; Jason Alan Fries; Matthew B. A. McDermott; Nigam H. Shah (CoRR, 2024)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam H. Shah (CoRR, 2024)

A multi-center study on the adaptability of a shared foundation model for electronic health records. - Lin Lawrence Guo; Jason Alan Fries; Ethan Steinberg; Scott Lanyon Fleming; Keith E. Morse; Catherine Aftandilian; José D. Posada; Nigam Shah; Lillian Sung (npj Digit. Medicine, 2024)

Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare. - Lin Lawrence Guo; Keith E. Morse; Catherine Aftandilian; Ethan Steinberg; Jason Alan Fries; José D. Posada; Scott Lanyon Fleming; Joshua Lemmon; Karim Jessa; Nigam Shah; Lillian Sung (BMC Medical Informatics Decis. Mak., 2024)

Time-to-Event Pretraining for 3D Medical Imaging. - Zepeng Frazier Huo; Jason Alan Fries; Alejandro Lozano; Jeya Maria Jose Valanarasu; Ethan Steinberg; Louis Blankemeier; Akshay S. Chaudhari; Curtis P. Langlotz; Nigam Shah (ICLR, 2025)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam Shah (ICLR, 2025)