• K L Sujitha
• Devatha Shivshyl
• Chagi Vijetha
• Chithra

Imminent need of turning huge amount of available health data into useful information and knowledge attracts data mining techniques in medical diagnosis process. Data mining is a procedure of distinguishing and extracting valuable data and setting up connection between attributes in substantial datasets. Existing health disease prediction models use one or multiple data mining techniques. This paper surveys heart disease prediction systems systematically where in techniques are compiled, tabulated and analyzed based on hybrid techniques categorization. In this paper, the techniques are classified into two main categories: Discrete and Integrated, which are further classified as supervised, unsupervised, hybrid and miscellaneous. It is revealed from this survey, even though usage of one data mining technique performs well, hybrid data mining techniques yield promising outcomes in the determination of coronary illness.

Data mining, Health disease prediction (HDP).

"A Survey on Smart Health Prediction Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.e296-e301, February-2023, Available :http://www.jetir.org/papers/JETIR2302435.pdf

"A Survey on Smart Health Prediction Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppe296-e301, February-2023, Available at : http://www.jetir.org/papers/JETIR2302435.pdf