Keith E. Morse

According to our database, Keith E. Morse authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., December, 2024

Learning competing risks across multiple hospitals: one-shot distributed algorithms.

Dazheng Zhang, Jiayi Tong, Naimin Jing, Yuchen Yang, Chongliang Luo, Yiwen Lu, Dimitri A. Christakis, Diana Güthe, Mady Hornig, Kelly J. Kelleher, Keith E. Morse, Colin M. Rogerson, Jasmin Divers, Raymond J. Carroll, Christopher B. Forrest, Yong Chen

J. Am. Medical Informatics Assoc., 2024

Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems.

Alison Callahan, Duncan C. McElfresh, Juan M. Banda, Gabrielle Bunney, Danton Char, Jonathan H. Chen, Conor K. Corbin, Debadutta Dash, Norman L. Downing, Sneha S. Jain, Nikesh Kotecha, Jonathan Masterson, Michelle M. Mello, Keith E. Morse, Srikar Nallan, Abby Pandya, Anurang Revri, Aditya Sharma, Christopher D. Sharp, Rahul Thapa, Michael Wornow, Alaa Youssef, Michael A. Pfeffer, Nigam H. Shah

CoRR, 2024

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, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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., November, 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., May, 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 Goldstein, Jennifer L. Carlson, Ethan Steinberg, Austin Powell, Natalie M. Pageler, Keith E. Morse

Appl. Clin. Inform., March, 2023

A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records.

Lin Lawrence Guo, Jason A. Fries, Ethan Steinberg, Scott Lanyon Fleming, Keith E. Morse, Catherine Aftandilian, José D. Posada, Nigam Shah, Lillian Sung

CoRR, 2023

2022

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

Proceedings of the Machine Learning for Health, 2022

2021

A survey of extant organizational and computational setups for deploying predictive models in health systems.

Sehj Kashyap, Keith E. Morse, Birju S. Patel, Nigam H. Shah

J. Am. Medical Informatics Assoc., 2021