Rashid Ebrahim Al-Mannai, Mohammed Hamad Almerekhi, Mohammed Abdulla Al-Mannai, Mishahira N, K. K. Sadasivuni, H. Yalcin, H. Ouakad, I. Bahadur, S. Al-Maadeed, Asiya Albusaidi
{"title":"Artificial Intelligence in Predicting Heart Failure","authors":"Rashid Ebrahim Al-Mannai, Mohammed Hamad Almerekhi, Mohammed Abdulla Al-Mannai, Mishahira N, K. K. Sadasivuni, H. Yalcin, H. Ouakad, I. Bahadur, S. Al-Maadeed, Asiya Albusaidi","doi":"10.29117/quarfe.2021.0130","DOIUrl":null,"url":null,"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","PeriodicalId":9295,"journal":{"name":"Building Resilience at Universities: Role of Innovation and Entrepreneurship","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Building Resilience at Universities: Role of Innovation and Entrepreneurship","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29117/quarfe.2021.0130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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