Machine Learning Based System for Disease Detection and Personalised Health Recommendation

DOI

10.2991/978-94-6463-738-0_42How to use a DOI?

Keywords

Machine Learning; Diabetes; streamlitCardio vascular Disease; Parkinsonism Disease; SVM; Logistic Regression

Abstract

A Multi Disease Prediction System, or MDPS, uses cool machine learning methods! We focus on algorithms like Logistic Regression & Support Vector Machines (SVM) to predict specific diseases. Imagine a tool that’s easy to use; that’s made possible with the Streamlit library. The main goal? To create handy and smart way to spot multiple diseases early. This could really boost personalized healthcare!. In this article, we explore three conditions: diabetes mellitus, Cardiovascular disease, & Parkinsonism. We look at basic info. A model helps us accurately find risk factors for each disease. This research shows just how powerful machine learning can be in predicting multiple diseases and improving public health! Our training model learns from example data to make its predictions. Sure, there are many algorithms and methods out there for predicting diseases, but finding one system that can handle multiple diseases isn’t easy. That’s why we focus on using machine learning for multi-disease predictions in this paper. With this approach, we can make better predictions about diseases.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - K. B. Kiruthik
AU  - R. Ivenroche
AU  - C. Manimegalai
AU  - A. Inbavalli
PY  - 2025
DA  - 2025/06/22
TI  - Machine Learning Based System for Disease Detection and Personalised Health Recommendation
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 521
EP  - 534
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_42
DO  - 10.2991/978-94-6463-738-0_42
ID  - Kiruthik2025
ER  -