Multiple Health Disease Prediction
Keywords:
Machine Learning, SVM, Random Forest, Gradient BoostingAbstract
Predicting multiple health diseases using machine learning (ML) has become increasingly vital for early diagnosis and intervention. The proposed solution focuses on developing robust and accurate predictive models that can simultaneously forecast the likelihood of multiple health conditions based on individual patient data. The dataset comprises diverse health parameters, including lifestyle factors, and clinical indicators.
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Published
25-05-2024
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Articles
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Copyright (c) 2024 Anusha Benchalli, Apurva Jigajinni, Pragati Sawkar, Prajwal Trivedi, Sadhana P. Bangarashetti

This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
[1]
A. Benchalli, A. Jigajinni, P. Sawkar, P. Trivedi, and S. P. Bangarashetti, “Multiple Health Disease Prediction”, IJRESM, vol. 7, no. 5, pp. 161–167, May 2024, Accessed: Sep. 13, 2025. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/3048