Complex Event Processing of Health Data in Real Time Predicting Heart Failure Risk
Manaswini Sudhal1, Deepak Gupta2
1Manaswini Sudhal, Department of Computer Engineering, Siddhant College of Engineering Sadumbre, Pune, India.
2Prof. Dr. Deepak Gupta, Department of Computer Engineering, Siddhant College of Engineering Sadumbre, Pune, India.
Manuscript received on 15 August 2019. | Revised Manuscript received on 21 August 2019. | Manuscript published on 30 September 2019. | PP: 8623-8627 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6448098319/2019©BEIESP | DOI: 10.35940/ijrte.C6448.098319
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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: In this article, we develop a scalable system that can perform heart failure prediction techniques based on complex event processing (CEP). The emergence of different health conditions can be seen as complex events and therefore this concept can be easily extended to other uses. The system uses MLP (Multilayer Perceptron) for the prediction of heart failure. First, perform preprocessing and after that collect the health parameter. The system monitors the patients of heart failure and predicts heart attacks. When critical conditions are occurs the system warns the patients. Experimental results show that MLP is more accurate than C 4.5, based on Precision-Recall and F1.
Keywords: Complex Event Processing, Heart Failures Prediction, C4.5, and Multilayer Perceptron.
Scope of the Article: Signal and Speech Processing