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All Journal International Journal of Advanced Science and Computer Applications
Sandeep Kumar
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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A Machine Learning-Based Recommendation System for Disease Prediction Sonali Dass; Khushi Jaiswal; Sandeep Kumar
International Journal of Advanced Science and Computer Applications Vol. 5 No. 1 (2026): March 2026
Publisher : Utan Kayu Publishins

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ijasca.v5i1.121

Abstract

A key strategy for enhancing clinical judgment and tailored medicine is the incorporation of machine learning into healthcare systems. This study presents a Medicine Recommendation System (MRS) that uses a variety of machine learning models to recommend drugs based on disease prediction. Among these models are K-Means Clustering, Random Forest, Support Vector Classifier (SVC), Naive Bayes, Logistic Regression, and Gradient Boosting. In order to anticipate the likely condition and provide a suitable drug, the system makes use of patient data, including symptoms, demographics, and medical history. Accuracy, precision, recall, F1 score, and confusion matrix measures are used to assess each model's performance.
Co-Authors Khushi Jaiswal Sonali Dass