Decision Support Systems in HF based on Deep Learning Technologies.

Journal: Current heart failure reports
Published Date: Feb 10, 2022

Abstract

PURPOSE OF REVIEW: Application of deep learning (DL) is growing in the last years, especially in the healthcare domain. This review presents the current state of DL techniques applied to electronic health record structured data, physiological signals, and imaging modalities for the management of heart failure (HF), focusing in particular on diagnosis, prognosis, and re-hospitalization risk, to explore the level of maturity of DL in this field.

Authors

  • Marco Penso
    Department of Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy. Electronic address: marco.penso@cardiologicomonzino.it.
  • Sarah Solbiati
    Department of Electronics, Information and Biomedical Engineering, Politecnico Di Milano, P.zza L. da Vinci 32, 20133, Milan, Italy.
  • Sara Moccia
    Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Milan, Italy; Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy. Electronic address: sara.moccia@iit.it.
  • Enrico G Caiani
    Department of Electronics, Information and Biomedical Engineering, Politecnico Di Milano, P.zza L. da Vinci 32, 20133, Milan, Italy. enrico.caiani@polimi.it.

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