International Journal on Science and Technology

E-ISSN: 2229-7677     Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.

Machine Learning Techniques Based Hybrid Model for Disease Prediction

Author(s) Neha Kukade, Sunil Gupta
Country India
Abstract This study evaluates machine learning algorithms like Decision Tree, Random Forest, Naive Bayes, and KNN for instant disease prediction using patient symptoms. It identifies the most accurate and reliable model to support early diagnosis in digital healthcare.
Keywords Machine Learning, Disease Prediction, Decision Tree, Random Forest, Naive Bayes, KNN, Healthcare, Medical Diagnosis
Field Engineering
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-06-08
DOI https://doi.org/10.71097/IJSAT.v16.i2.4586
Short DOI https://doi.org/g9pz76

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