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Machine Learning and the Future of Cardiovascular Care

Quer, Giorgio ; Arnaout, Ramy ; Henne, Michael ; Arnaout, Rima

Journal of the American College of Cardiology, 2021-01, Vol.77 (3), p.300-313 [Periódico revisado por pares]

Elsevier Inc

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  • Título:
    Machine Learning and the Future of Cardiovascular Care
  • Autor: Quer, Giorgio ; Arnaout, Ramy ; Henne, Michael ; Arnaout, Rima
  • Assuntos: artificial intelligence ; bibliometric analysis ; cardiology ; deep learning ; literature search ; machine learning
  • É parte de: Journal of the American College of Cardiology, 2021-01, Vol.77 (3), p.300-313
  • Descrição: The role of physicians has always been to synthesize the data available to them to identify diagnostic patterns that guide treatment and follow response. Today, increasingly sophisticated machine learning algorithms may grow to support clinical experts in some of these tasks. Machine learning has the potential to benefit patients and cardiologists, but only if clinicians take an active role in bringing these new algorithms into practice. The aim of this review is to introduce clinicians who are not data science experts to key concepts in machine learning that will allow them to better understand the field and evaluate new literature and developments. The current published data in machine learning for cardiovascular disease is then summarized, using both a bibliometric survey, with code publicly available to enable similar analysis for any research topic of interest, and select case studies. Finally, several ways that clinicians can and must be involved in this emerging field are presented. [Display omitted] •ML algorithms can find sophisticated patterns in medical data and have the potential to improve cardiovascular care.•Cardiologists must take an active role in shaping how ML is used in cardiovascular practice and research.•To empower cardiologists in this role, we provide a framework to help critically evaluate developments in ML.•We also provide an open-source bibliometric survey of ML in cardiology.
  • Editor: Elsevier Inc
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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