Proceedings of the 2nd International Conference on Sustainable Business Practices and Innovative Models (ICSBPIM-2025)

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Machine Learning-Driven Medical Recommendation System for Early Disease Prediction and Personalized Treatment

Authors
Gaurav Singh Negi1, *, Surya Kant Pal1, Utpal Dhar Das1, Saloni Srivastava1, Hari Shankar Shyam2
1Department of Mathematics & Data Science, SSES, Sharda University, Greater Noida, 201310, UP, India
2Sharda School of Business Studies, Sharda University, Greater Noida, Uttar Pradesh, India
*Corresponding author. Email: negigaurav746@gmail.com
Corresponding Author
Gaurav Singh Negi
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-872-1_63How to use a DOI?
Keywords
K-Nearest Neighbors; RandomForest; Robust; Healthcare; Accuracy
Abstract

This project presents an intelligent Naive Bayes and K-Nearest Neighbors (KNN) based medical recommendation system to diagnose a disease based on symptoms provided by patients and prescribe personalized medicine. Using effective strategies such as feature encoding and balancing data; the system operates with high efficiency across different clinical data sets. Experimental results show the Naive Bayes model attains a striking accuracy rate of 96% compared to KNN and popular algorithms such as Random Forest because it operates smoothly with categorical features. The system not only efficiently diagnoses disease patterns with satisfactory accuracy but also effectively provides recommendations such as precautions, medicines, and lifestyle change and assists doctors with a robust decision- support system. This project explains how machine learning can enhance accuracy in diagnosis, reduce human mistakes, and benefit patients and how it provides future directions in developing AI-based health care solutions.

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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Volume Title
Proceedings of the 2nd International Conference on Sustainable Business Practices and Innovative Models (ICSBPIM-2025)
Series
Advances in Economics, Business and Management Research
Publication Date
4 November 2025
ISBN
978-94-6463-872-1
ISSN
2352-5428
DOI
10.2991/978-94-6463-872-1_63How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Gaurav Singh Negi
AU  - Surya Kant Pal
AU  - Utpal Dhar Das
AU  - Saloni Srivastava
AU  - Hari Shankar Shyam
PY  - 2025
DA  - 2025/11/04
TI  - Machine Learning-Driven Medical Recommendation System for Early Disease Prediction and Personalized Treatment
BT  - Proceedings of the 2nd International Conference on Sustainable Business Practices and Innovative Models (ICSBPIM-2025)
PB  - Atlantis Press
SP  - 1028
EP  - 1043
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-872-1_63
DO  - 10.2991/978-94-6463-872-1_63
ID  - Negi2025
ER  -