Mohamed Elhoseny1, Mazin Abed Mohammed2,*, Salama A. Mostafa3, Karrar Hameed Abdulkareem4, Mashael S. Maashi5, Begonya Garcia-Zapirain6, Ammar Awad Mutlag7, Marwah Suliman Maashi8
CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 51-71, 2021, DOI:10.32604/cmc.2021.012632
Abstract Heart disease (HD) is a serious widespread life-threatening disease. The heart of patients with HD fails to pump sufficient amounts of blood to the entire body. Diagnosing the occurrence of HD early and efficiently may prevent the manifestation of the debilitating effects of this disease and aid in its effective treatment. Classical methods for diagnosing HD are sometimes unreliable and insufficient in analyzing the related symptoms. As an alternative, noninvasive medical procedures based on machine learning (ML) methods provide reliable HD diagnosis and efficient prediction of HD conditions. However, the existing models of automated ML-based HD diagnostic methods cannot satisfy… More >
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