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      Stacked Bi-directional LSTM Layer Based Model for Prediction of Possible Heart Disease during Lockdown Period of COVID-19

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          Abstract

          Cardiovascular disease (CVD) affects the walls of the arteries that supply the myocardium. CVD is not a single disease. It is a cluster of diseases and injuries that affect the cardiovascular system i.e. the heart and blood vessels. Heart failure is concern in patients with COVID-19. Alternately mental anxiety during lockdown period od COVID-19 may increase CVD. For assisting health care system, an automated tool is proposed in this paper that uses Reccurrent Neural Network (RNN). A stacked bi-directional LSTM layer based model is proposed in this paper that considers interfering factors from past health records while detecting patients with cardiac problems. Experimental results have indicated promising accuracy of 93.22% in predicting patients with cardiac troubles.

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          Author and article information

          Journal
          ScienceOpen Preprints
          ScienceOpen
          23 June 2020
          Affiliations
          [1 ] The Bhawanipur Education Society College
          Article
          10.14293/S2199-1006.1.SOR-.PPQFHL4.v1

          This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

          All data generated or analysed during this study are included in this published article (and its supplementary information files).

          Computer science

          Mental Anxiety, Cardiovascular disease, CVD, Neural Network, RNN, Deep Learning, Stacked Bi-LSTM, Cardiac troubles, COVID-19

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