Machine Learning Techniques Based Hybrid Model for Disease Prediction

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.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-06-08
DOI
https://doi.org/10.71097/ijsat.v16.i2.4586
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Machine Learning Techniques Based Hybrid Model for Disease Prediction

S. K. Gupta, Neha Kukade -
International Journal on Science and Technology
Artificial Intelligence in Healthcare
article

Machine Learning Techniques Based Hybrid Model for Disease Prediction

S. K. Gupta, Neha Kukade -
article en

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.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 84%
Artificial Intelligence in Healthcare
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Machine Learning Techniques Based Hybrid Model for Disease Prediction — S. K. Gupta, Neha Kukade - · International Journal on Science and Technology (2025) | TGRS Research Map | TGRS