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A Study on Implementation of different Data Mining Techniques on Healthcare
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 31 |
| Year of Publication: 2019 |
| Authors: Shabeena T. |
10.5120/ijca2019919116
|
Shabeena T. . A Study on Implementation of different Data Mining Techniques on Healthcare. International Journal of Computer Applications. 178, 31 ( Jul 2019), 13-17. DOI=10.5120/ijca2019919116
Abstract
Data mining is one of the richest areas of research that is more popular in health organizations. It is the process of pattern discovery and extraction where huge amount of data is involved. The data generated by the health organizations are very vast and complex. This data contains details regarding hospitals, patients, medical claims, treatment cost etc. So, there is a need to generate a powerful tool for analyzing and extracting important information from this complex data. Disease prediction plays an important role in data mining. More data mining classification algorithms like decision trees, neural networks, Bayesian classifiers, Support vector machines, etc are used to diagnosis the heart diseases. The aim of this paper is to summarize some of the current research on predicting heart diseases using different data mining techniques, analyze the various combinations of mining algorithms used and conclude which technique(s) are effective and efficient.
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