Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach.

Journal: Journal for immunotherapy of cancer
Published Date: Oct 1, 2021

Abstract

BACKGROUND: Treatment with immune checkpoint inhibitors (ICIs) has been associated with an increased rate of cardiac events. There are limited data on the risk factors that predict cardiac events in patients treated with ICIs. Therefore, we created a machine learning (ML) model to predict cardiac events in this at-risk population.

Authors

  • Samuel Peter Heilbroner
    Data Science, ConcertAI, New York, New York, USA sheilbroner@concertai.com.
  • Reed Few
    Data Science, ConcertAI, New York, New York, USA.
  • Judith Mueller
    Data Science, ConcertAI, New York, New York, USA.
  • Jitesh Chalwa
    Data Science, ConcertAI, New York, New York, USA.
  • Francois Charest
    Data Science, ConcertAI, New York, New York, USA.
  • Somasekhar Suryadevara
    Data Science, ConcertAI, New York, New York, USA.
  • Christine Kratt
    Bristol Myers Squibb, New York, New York, USA.
  • Andres Gomez-Caminero
    Bristol Myers Squibb, New York, New York, USA.
  • Brian Dreyfus
    Bristol Myers Squibb, New York, New York, USA.
  • Tomas G Neilan
    Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.

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