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    Artificial Intelligence in Predicting Heart Failure

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    Date
    2021
    Author
    Al-Mannai, Rashid Ebrahim
    Almerekhi, Mohammed Hamad
    Al-Mannai, Mohammed Abdulla
    N, Mishahira
    Sadasivuni, Kishor Kumar
    Yalcin, Huseyin Cagatay
    Ouakad, Hassen M.
    Bahadur, Issam
    Al-Maadeed, Somaya
    Albusaidi, Asiya
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    Abstract
    Heart Failure is a major chronic disease that is increasing day by day and a great health burden in health care systems world wide. Artificial intelligence (AI) techniques such as machine learning (ML), deep learning (DL), and cognitive computer can play a critical role in the early detection and diagnosis of Heart Failure Detection, as well as outcome prediction and prognosis evaluation. The availability of large datasets from difference sources can be leveraged to build machine learning models that can empower clinicians by providing early warnings and insightful information on the underlying conditions of the patients
    URI
    https://doi.org/10.29117/quarfe.2021.0130
    DOI/handle
    http://hdl.handle.net/10576/24415
    Collections
    • Biomedical Research Center Research [‎786‎ items ]
    • Center for Advanced Materials Research [‎1486‎ items ]
    • Computer Science & Engineering [‎2428‎ items ]
    • Mechanical & Industrial Engineering [‎1461‎ items ]
    • Theme 2: Health and Biomedical Sciences [‎80‎ items ]

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