• Prem Kumar Rathaor

Health care informatics has benefited from the proliferation of new applications made possible by advances in information technology. Massive amounts of information are being produced through health care informatics. Data mining methods applied to these datasets will allow for disease forecasting. Data mining is the practice of systematically acquiring new information from existing data by means of automated analysis and the presentation of the resulting knowledge. Association, grouping, classification, and prediction are all examples of data mining methods. Health care data and illness prediction are examined using several data mining technologies, and their results are compared. Data mining is an interdisciplinary field that incorporates techniques from a wide range of other fields, such as data visualization, machine learning, database administration, statistics, and many more. It is possible to have these methods cooperate with one another in order to solve more complicated issues. In general, software or systems designed for data mining will make use of one or more of these approaches in order to cope with the various data needs, kinds of data, application areas, and mining jobs.

Data Mining, Fundamentals of Data Mining, Data Mining Techniques, Healthcare,

"A Study on Data Mining's Machine Learning-Based Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.a387-a392, July-2023, Available :http://www.jetir.org/papers/JETIR2307045.pdf

"A Study on Data Mining's Machine Learning-Based Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppa387-a392, July-2023, Available at : http://www.jetir.org/papers/JETIR2307045.pdf