Multi-Disease Detection with Doctor Recommendation System
DOI:
https://doi.org/10.47392/IRJAEH.2025.0062Keywords:
Exploratory data analysis (EDA), k-Nearest Neighbours algorithm (KNN), Logistic regression, Streamlit Cloud, Support vector machine (SVM).Abstract
AI and machine learning, from self-driving cars to health care, have turned out to be an indispensable tool for several industries. In medicine, the big availability of patient records now opens new possibilities for applying techniques of machine learning for disease detection and diagnosis at earlier stages. The main objective of this work is to provide an advanced prediction system capable of detecting multiple diseases. This will overcome one of the major disadvantages of most systems, which usually target single diseases and may or may not do so very accurately. Our system will target the following major five diseases: Heart Disease, Liver Disease, Diabetes, Lung Cancer, and Parkinson's Disease-specifically, although it has the flexibility for future gains on other conditions. The following project incorporates different disease-specific parameters, wherein a user can enter their health data to get accurate predictions of the presence of a disease. This project would have a greater influence on enabling people to monitor and take precautions for better maintenance of health, thereby helping to increase the life span of an individual. In using machine learning in this respect, such a system may support individual well-being by providing the most accurate disease predictions possible, saving lives if that be the case.
Downloads
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Research Journal on Advanced Engineering Hub (IRJAEH)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.