Aaron Eisman

MD-PhD Candidate in Biomedical Informatics at Brown University

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I am an eighth-year MD-PhD candidate in Biomedical Informatics and Computational Biology training under the direction of Neil Sarkar at the Center for Biomedical Informatics at Brown University.

My research interests focus on the development of informatics methods that leverage population-level data to improve the accuracy of cardiovascular disease risk estimation towards a learning healthcare system. My work aims to improve adherence to clinical practice guidelines, enhance the precision of preventative medical therapies, better explain observed health outcome disparities in racial and ethnic minority populations, and develop mechanisms for translating omics research into clinical medical practice. I received an Sc.B. from Brown University in Applied Mathematics.

Before returning to Brown, I spent two years as a clinical research coordinator for the Cardiopulmonary Exercise Laboratory at Massachusetts General Hospital. As a member of that research team, we worked to understand cardiovascular pathophysiology including heart failure and pulmonary hypertension using exercise as a physiologic probe. Among other projects, we demonstrated that increased pulmonary capillary wedge pressure relative to cardiac output during exercise predicts exercise capacity and heart failure outcomes.

selected publications

  1. Clinical Note Section Detection Using a Hidden Markov Model of Unified Medical Language System Semantic Types
    Aaron S Eisman, Katherine A Brown, Elizabeth S Chen, and 1 more author
    AMIA Annual Symposium Proceedings 2021
  2. Extracting Angina Symptoms from Clinical Notes Using Pre-Trained Transformer Architectures
    Aaron S Eisman, Nishant R Shah, Carsten Eickhoff, and 4 more authors
    AMIA Annual Symposium Proceedings 2020
  3. Pulmonary Capillary Wedge Pressure Patterns During Exercise Predict Exercise Capacity and Incident Heart Failure
    Aaron S Eisman, Ravi V Shah, Bishnu P Dhakal, and 9 more authors
    Circulation. Heart failure May 2018
  4. An Automated System for Categorizing Transthoracic Echocardiography Indications According to the Echocardiography Appropriate Use Criteria
    Aaron S Eisman, Rory B Weiner, Elizabeth S Chen, and 4 more authors
    AMIA Annual Symposium Proceedings May 2017