Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

Journal: Methods of information in medicine
Published Date:

Abstract

BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previously observed that a few genetic cardiac diseases can be separated from each other and healthy controls by applying machine learning to Ca transient signals measured from iPSC-derived cardiomyocytes (CMs).

Authors

  • Henry Joutsijoki
    Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.
  • Kirsi Penttinen
    Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
  • Martti Juhola
    Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.
  • Katriina Aalto-Setälä
    Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.