PERFORMANCE COMPARISON OF CLASSICAL ALGORITHMS AND DEEP NEURAL NETWORKS FOR TUBERCULOSIS PREDICTION
This study compares the performance of several classical machine learning algorithms and deep neural networks for the prediction of tuberculosis in the Democratic Republic of Congo (DRC), using a sample of 1000 cases including clinical and demographic data. The sample is divided into two sets: 80% f...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Community Service Research Center (LPPM) STMIK Nusa Mandiri Jakarta
2025-01-01
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| Series: | Techno Nusa Mandiri: Journal of Computing and Information Technology |
| Subjects: | |
| Online Access: | https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/5609 |
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