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Data Mining is an famous and powerful technology which is of high interest in today’s computer world. It uses already existing data in different databases and transform it into new technology and research. It extracts new patterns for large datasets and the knowledge associated with these patterns. There is a large amount of data available within the healthcare due to availability of computer systems. The most important and popular data processing techniques are classification, association, clustering, prediction and patterns. In healthcare concern businesses, data processing plays a crucial role in early prediction of diseases. In general, to detect a disease numerous health related tests must be conducted in a patient. The usage of knowledge mining techniques in disease prediction is to scale back the test and increase the accuracy of rate of detection of disease. This research paper intends to supply a survey of current techniques of data discovery in databases using data processing techniques that are in use in today’s medical research particularly in Diabetes and liver Disease Prediction. The major objective of this paper is to evaluate data mining techniques in healthcare application to develop an accurate decisions.


Pre-processing, prediction, classification

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How to Cite
Prof. Swati Powar, Ms. Ashwini Patil, Ms. Shrushti Desai, and Mr.Ashish Singh, “HEALTHCARE DECISION SUPPORT SYSTEM FOR DISEASE PREDICTION”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 6, Jun. 2020.


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