Resources


Database Credentialed Access

AMR-UTI: Antimicrobial Resistance in Urinary Tract Infections

Michael Oberst, Soorajnath Boominathan, Helen Zhou, Sanjat Kanjilal, David Sontag

AMR-UTI is a freely accessible dataset, derived from electronic health record (EHR) information on over 100,000 urinary tract infections (UTI) treated at Massachusetts General Hospital and Brigham & Women's Hospital in Boston, MA, USA.

antibiotic resistance causal inference policy learning antimicrobial resistance urinary tract infection clinical decision support machine learning

Published: Nov. 4, 2020. Version: 1.0.0

Database Credentialed Access

AMR-UTI: Antimicrobial Resistance in Urinary Tract Infections

Michael Oberst, Soorajnath Boominathan, Helen Zhou, Sanjat Kanjilal, David Sontag

AMR-UTI is a freely accessible dataset, derived from electronic health record (EHR) information on over 100,000 urinary tract infections (UTI) treated at Massachusetts General Hospital and Brigham & Women's Hospital in Boston, MA, USA.

antibiotic resistance causal inference policy learning antimicrobial resistance urinary tract infection clinical decision support machine learning

Published: Nov. 4, 2020. Version: 1.0.0

Database Credentialed Access

AMR-UTI: Antimicrobial Resistance in Urinary Tract Infections

Michael Oberst, Soorajnath Boominathan, Helen Zhou, Sanjat Kanjilal, David Sontag

AMR-UTI is a freely accessible dataset, derived from electronic health record (EHR) information on over 100,000 urinary tract infections (UTI) treated at Massachusetts General Hospital and Brigham & Women's Hospital in Boston, MA, USA.

antibiotic resistance causal inference policy learning antimicrobial resistance urinary tract infection clinical decision support machine learning

Published: Nov. 4, 2020. Version: 1.0.0

Database Credentialed Access

Predictors of Hospital Onset Infection: A Matched Retrospective Cohort Dataset

Ziming Wei, Luke Sagers, Caroline McKenna, Ted Pak, Chanu Rhee, Michael Klompas, Sanjat Kanjilal

NPA-CP is a freely accessible dataset derived from electronic health record (EHR) information at MGB between 2015 and 2024. The dataset includes 11 different pathogens and can be used to predict hospital-onset infections for these pathogens.

electronic health records infection control clinical machine learning infectious diseases hospital onset infection colonization pressure

Published: Nov. 4, 2025. Version: 1.0.0