Retinal Arteriovenous Information Improves the Prediction Accuracy of Deep Learning-Based baPWV Index From Color Fundus Photographs.

Journal: Investigative ophthalmology & visual science
PMID: 39998460

Abstract

PURPOSE: To compare the prediction accuracy of brachial-ankle pulse wave velocity (baPWV) from color fundus photographs (CFPs) using different deep learning models.

Authors

  • Michiyuki Saito
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Mizuho Mitamura
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Kanae Fukutsu
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Dong Zhenyu
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Ryo Ando
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Satoru Kase
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Satoshi Katsuta
    Teine Keijinkai Hospital, Sapporo, Japan.
  • Susumu Ishida
    Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.

Keywords

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