Predicting Diabetes Mellitus with Machine Learning Techniques
This study addresses the challenge of accurately identifying diabetes mellitus in individuals. Utilizing accessible online and real-world diagnostic data, we employ machine learning models, including Support Vector Machine, Random Forest, Naïve Bayes, eXtreme Gradient Boosting, and Deep Neural Netwo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MMU Press
2024-03-01
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| Series: | Journal of Engineering Technology and Applied Physics |
| Subjects: | |
| Online Access: | https://journals.mmupress.com/index.php/jetap/article/view/974/523 |