DATA Mining Application to wards Adverse Effects of Anti-Diabetic Drugs
Gopishetti Venkatesh1, M. Lawanyashri2, Sai Saraswathi V3
1Gopishetti Venkatesh, School of Information Technology, VIT, Institute of Technology Vellore (Tamil Nadu), India.
2Dr. M. Lawanyashri, School of Information Technology, VIT, Institute of Technology Vellore (Tamil Nadu), India.
3Dr. Sai Saraswathi V, School of Advanced Sciences, VIT, Institute of Technology Vellore (Tamil Nadu), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 2544-2546 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5739058719/19©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: Data mining applications in health care information system is the trend set and shaping the IT industries. Data mining techniques for Anti-Diabetic Drugs is a new side of application which plays a major role in health care information system. We all wanted to know how a person is been affected by the particular medicine. Usually, many researchers are trying to predict the diseases using data mining algorithms but at the same time we have to take into consideration how the drugs are affecting a particular person. It helps a doctor to analyse these results to treat them in a proper way. The implementation can be done through the predictive data mining techniques like Decision Tree Induction, J48 classifier and Naive Bayes classifier algorithms. It predicts whether there is any change that has occurred or not after having the medicine i.e., impact, it also predicts the percentage to which, it has been cured.
Keyword: Classification, Diseases Diagnosis, Predictive Data Mining, Naïve Bayes Classifier, Impact.
Scope of the Article: Data Mining