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Research Paper | Computer Engineering | Volume 15 Issue 5, May 2026 | Pages: 1313 - 1320 | India
Multiple Disease Prediction System
Abstract: This study presents a web-based Multiple Disease prediction system designed for early detection of heart disease, diabetes, and Parkinson's disease using machine learning and deep learning techniques. The system integrates Random Forest for heart disease prediction and Artificial Neural Networks for diabetes and Parkinson's disease analysis. A hybrid risk assessment mechanism combines model predictions with symptom severity, lifestyle habits, and family medical history to improve practical reliability. The platform is implemented using Flask, HTML/CSS, SQLite, and an NLP-based chatbot using TF-IDF and cosine similarity for user assistance. Experimental evaluation demonstrates improved prediction efficiency and usability for preventive healthcare applications. The proposed system provides an accessible and scalable digital healthcare solution for early risk assessment and health awareness.
Keywords: Multiple Disease Prediction System, Healthcare Analytics, Machine Learning, Deep Learning, Artificial Neural Network (ANN), Random Forest, Risk Assessment, Digital Healthcare
How to Cite?: Aditya Sharad Dhumal, Rohan Rajkumar Gutal, Vivek Hanumant Khande, Harsh Hemant Randhave, "Multiple Disease Prediction System", Volume 15 Issue 5, May 2026, International Journal of Science and Research (IJSR), Pages: 1313-1320, https://www.ijsr.net/getabstract.php?paperid=SR26516115545, DOI: https://dx.dx.doi.org/10.21275/SR26516115545