Prediction of Genotype Positivity in Patients With Hypertrophic Cardiomyopathy Using Machine Learning.

Journal: Circulation. Genomic and precision medicine
Published Date: Jun 1, 2021

Abstract

BACKGROUND: Genetic testing can determine family screening strategies and has prognostic and diagnostic value in hypertrophic cardiomyopathy (HCM). However, it can also pose a significant psychosocial burden. Conventional scoring systems offer modest ability to predict genotype positivity. The aim of our study was to develop a novel prediction model for genotype positivity in patients with HCM by applying machine learning (ML) algorithms.

Authors

  • Lusha W Liang
    Division of Cardiology, Department of Medicine (L.W.L., M.S.M., M.P.R., Y.J.S.), Columbia University Irving Medical Center, New York, NY.
  • Michael A Fifer
    Cardiology Division, Department of Medicine (M.A.F.), Massachusetts General Hospital, Boston.
  • Kohei Hasegawa
    Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America.
  • Mathew S Maurer
    Division of Cardiology, Department of Medicine (L.W.L., M.S.M., M.P.R., Y.J.S.), Columbia University Irving Medical Center, New York, NY.
  • Muredach P Reilly
    Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA.
  • Yuichi J Shimada
    Division of Cardiology, Department of Medicine (L.W.L., M.S.M., M.P.R., Y.J.S.), Columbia University Irving Medical Center, New York, NY.

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