Disease Prediction System Using Data Mining

Authors

  • Sanyukta Kankirad Sipna College of Engineering and Technology
  • Amruta Suralkar
  • Rutuja Sable
  • Puja Kohale
  • Neha Rathi

Keywords:

Prediction system, disease prediction, naive bayes, symptoms, data mining, structured data, text data

Abstract

The project's main goal is to develop a system that allows users to get personalized advice on their health problems using data mining techniques. In today's hectic world, most individuals overlook this asset, which could be due to a lack of time or the intricacy of the massive data available on the Internet. Our goal is to evaluate data processing techniques in clinical and health care settings in order to make informed decisions. Machine learning and database management are used in data mining to extract new patterns and knowledge linked to these patterns from large data sets. Particularly the task is to get data. The various parameters enclosed in data processing include path analysis and predictive analysis. Due to the availability of computers, a vast amount of information in the medical and health care disciplines is becoming accessible. Such an oversized amount of information can't be processed to make health predictions in the early stage and make treatment schedules to diagnose. It's a cutting-edge, powerful technology that's generating a lot of buzz in the computer world. It reworks information from many databases into new research and outcomes.

Published

2022-05-20