A Review Article on the Prediction of Diseases at an Early Stage

Mohd Nadeem Khan; Mrs Ankita Srivastava

doi:10.55524/ijircst.2023.11.2.8

Authors

Mohd Nadeem Khan M.Tech. Scholar, Department of Computer Science and Engineering, Integral University, Lucknow, India Author
Mrs Ankita Srivastava Assistant Professor, Department of Computer Science and Engineering, Integral University Lucknow, India Author

DOI:

https://doi.org/10.55524/ijircst.2023.11.2.8

Keywords:

Disease Prediction, Machine Learning, Healthcare, Random Forest

Abstract

Individuals today suffer from a wide range of diseases as a result of their lifestyle choices and the environment in which they live. The objective of forecasting disease at an earlier stage becomes an increasingly vital condition as the identification and prediction of such diseases at their earlier phases become highly significant. Most individuals are too lazy to go to the hospital or see a doctor for a small problem. Our approach focuses on accuracy to detect additional symptoms for illness prediction in healthcare. In this section, I've employed a variety of machine learning algorithms carefully and focused in this few, which achieved the highest accuracy with that specific condition in order to build a strong model that produces the most exact forecasts. This work introduces the topics of illness prediction, disease therapy, and local medical consultation with effective machine learning programming. There are several diseases in the world that are brought on by the conditions of people's living habits or their surroundings. Thus, this study offers a summary of machine learning based illness prediction.

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