Predicting the Risk of Heart Failure with EHR Sequential Data Modeling
Vamsidhar Talasila1, Rajesh Kumar T2, Ch. Pooja Sai3, S. Satya Sai4, Yalanti Ayyappa5
1Vamsidhar Talasila, Assistant Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
2Rajesh Kumar T, Assistant Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
3Ch. Pooja Sai, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
4S. Satya Sai, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
5Yalanti Ayyappa, Assistant Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (Andhra Pradesh), India.
Manuscript received on 04 May 2019 | Revised Manuscript received on 16 May 2019 | Manuscript Published on 23 May 2019 | PP: 458-461 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F10780476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Coronary contamination is a savage infection that massive hundreds of people across the world encounters. at the same time as thinking about downfall costs and massive variety of those who encounters coronary illness, it’s far located how important early assure of coronary infection. standard technique for studies isn’t always extraordinary for such a sickness. operating up a recuperation investigation shape trouble to ai for desire for coronary disease offers extra careful give up than stylish manner. in this paper, a coronary ailment desire structure which uses faux neural framework backpropagation figuring is proposed. 13 scientific capabilities were used as dedication for the neural framework and sooner or later the neural framework modified into installation with backpropagation figuring to assume nonappearance or proximity of coronary sickness with accuracy of ninety five%.
Keywords: Matlab, Entropy Estimation.
Scope of the Article: Streaming Data