Analisis Performa Metode Yolo Untuk Deteksi Hyperlipidemia Berdasarkan Klasifikasi Citra Corneal Arcus
Abstract
Hyperlipidemia is a medical condition with high blood lipid levels that increase the risk of cardiovascular disease. A physical indicator of hyperlipidemia is Corneal Arcus, a white ring around the cornea. This study analyzes the ability of the YOLO (You Only Look Once) method to detect and classify Corneal Arcus in eye images. The dataset consists of 348 eye images in three categories: normal, at-risk, and Corneal Arcus. Results show the YOLO model achieved 88.9% accuracy in detecting Corneal Arcus, with precision, recall, F1-score, and mean average precision (MAP) of 88.9%, 89.2%, 88.8%, and 88.9%, respectively. These findings indicate significant potential for the YOLO method in technical applications within informatics. Although not yet validated for medical use, this research aims to share basic scientific ideas.
Keywords: YOLO; Hyperlipidemia; Corneal Arcus; Image Classification
Abstrak
Hyperlipidemia adalah kondisi medis dengan kadar lipid darah tinggi yang meningkatkan risiko penyakit Kardiovaskular. Indikator fisik hyperlipidemia adalah Corneal Arcus, cincin putih di sekitar kornea. Penelitian ini menganalisis kemampuan metode YOLO (You Only Look Once) dalam mendeteksi dan mengklasifikasikan Corneal Arcus pada citra mata. Dataset terdiri dari 348 gambar mata dalam tiga kategori: normal, berisiko, dan Corneal Arcus. Hasil menunjukkan model YOLO mencapai akurasi 88,9% dalam mendeteksi Corneal Arcus, dengan presisi, recall, F1-score, dan mean average precision (MAP) masing-masing sebesar 88,9%, 89,2%, 88,8%, dan 88,9%. Temuan ini menunjukkan potensi besar metode YOLO dalam aplikasi teknis di bidang informatika. Meskipun belum tervalidasi untuk penggunaan medis, hasil ini bertujuan untuk membagikan ide ilmiah dasar.
Kata kunci: YOLO; Hyperlipidemia; Corneal Arcus; Klasifikasi Citra;
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