Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures
Early screening for coronary heart disease (CHD) remains insufficiently addressed, underscoring the need for a more effective screening tool. Previous studies have reported a classification accuracy of only 72.73%, which is inadequate. This study aimed to develop and evaluate a machine learning mode...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Gadjah Mada
2025-02-01
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| Series: | Jurnal Nasional Teknik Elektro dan Teknologi Informasi |
| Subjects: | |
| Online Access: | https://jurnal.ugm.ac.id/v3/JNTETI/article/view/13658 |
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