Multi-Disease Prediction System Using Machine Learning

Vasepalli Kamakshamma, Gurram Mekhala Sumanth, Kesava Reddy Gari Nithin Kumar Reddy, Bhumannagari Pallavi, Chakala Sri Varshini

2025

Abstract

The healthcare industry is currently experiencing a significant imbalance, with a high patient-to-doctor ratio, posing challenges to effective patient care. In the age of healthcare digitization, using machine learning (ML) to forecast diseases has become essential for accurately identifying and effectively treating a variety of medical disorders. This paper examines how to use Django and machine learning to build a reliable multi-disease prediction system for diseases such as stroke, depression in students, and diabetes. Based on user input features, the system is trained to categorize and forecast the likelihood of various diseases using real-world medical datasets. Both healthcare experts and non-technical individuals can profit from the system thanks to the Django framework's smooth user interface. The paper also discusses crucial procedures including data preprocessing, model selection, training, and deployment, emphasizing how crucial recall and dependability are for predictive health solutions. By offering prompt medical action, it seeks to increase awareness of how these technologies can transform early diagnosis, lower healthcare costs, and ultimately improve patient outcomes.

Paper Citation

in Harvard Style

Kamakshamma V., Sumanth G., Reddy K., Pallavi B. and Varshini C. (2025). Multi-Disease Prediction System Using Machine Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 116-127. DOI: 10.5220/0013878600004919

in Bibtex Style

@conference{icrdicct`2525,
author={Vasepalli Kamakshamma and Gurram Sumanth and Kesava Reddy and Bhumannagari Pallavi and Chakala Varshini},
title={Multi-Disease Prediction System Using Machine Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={116-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013878600004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Multi-Disease Prediction System Using Machine Learning
SN - 978-989-758-777-1
AU - Kamakshamma V.
AU - Sumanth G.
AU - Reddy K.
AU - Pallavi B.
AU - Varshini C.
PY - 2025
SP - 116
EP - 127
DO - 10.5220/0013878600004919
PB - SciTePress