Big Data Based Diabetes and Heart Disease Prediction System by Employing Supervised Learning Algorithm
J. Agnes Beula Christy1, S. Appavu alias Balamurugan2
1J. Agnes Beula Christy*, Research Scholar, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu
2S. Appavu alias Balamurugan, Professor, Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu.
Manuscript received on November 19, 2019. | Revised Manuscript received on 28 November, 2019. | Manuscript published on December 10, 2019. | PP: 3398-3405 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6251129219/2019©BEIESP | DOI: 10.35940/ijitee.B6251.129219
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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: Healthcare systems generate bytes and bytes of data and the data growth is exponential. The voluminous data can be analysed effectively, only when the data organization is efficient. Additionally, data retrieval must also be made simpler, such that the healthcare professional can compare and contrast the test sample with the database of health records. This makes it possible to achieve better disease prediction and this work presents a big data based disease prediction system with the help of supervised learning. The proposed approach clusters the related health records, based on every medical attribute followed by which the disease is predicted by SVM classifier. The performance of the proposed disease prediction system is observed to be satisfactory in terms of accuracy, precision, recall, F-measure, while consuming reasonable period of time.
Keywords: Big Data, Disease Prediction, Supervised Learning, Database Server.
Scope of the Article: Big Data Analytics