Application of Data Mining In Healthcare and Current Issues

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Dr. Sanjivani Jadhao, Malhar Jadhao, Gauri Ajay Chaudhary, Priyanka Deshmukh, Dattu Hawale

Abstract

Quantitative and Qualitative exploration of clinical and diagnostic data using advanced analytics could unravel hidden medical knowledge by finding correlations, causations, and associations between apparently independent variables. Therefore, the scope and use and of Data Mining techniques in the current healthcare system is increasing steadily. In regard to this, we will discuss the disciplines, methods, models, algorithms, and results, and how these techniques would help in performing studies including but not limited to long-term prospective and retrospective studies, population studies, correlation studies, multicentric, multiracial, phased studies, meta-analysis, pharmacovigilance, etc. on Ayurvedic drugs and methods. We have discussed the applications of Data Mining on healthcare that are being implemented in developed countries. We have also discussed the issues like lack of quality data and record-keeping, and other issues and challenges in conducting ayurvedic studies in India, and how the National Digital Health Blueprint (NDHB) would be a game-changer in the current healthcare system of India.

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