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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Bibliografski detalji

Glavni autori:	Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho
Format:	Artigo
Jezik:	Inglês
Izdano:	Universitas Gadjah Mada 2025-02-01
Serija:	Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Teme:	coronary heart disease facial texture feature artificial neural network region of interest
Online pristup:	https://jurnal.ugm.ac.id/v3/JNTETI/article/view/13658
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