Use of explainable AI on slit-lamp images of anterior surface of eyes to diagnose allergic conjunctival diseases

Use of explainable AI on slit-lamp images of anterior surface of eyes to diagnose allergic conjunctival diseases

Background: Artificial intelligence (AI) is a promising new technology that has the potential of diagnosing allergic conjunctival diseases (ACDs). However, its development is slowed by the absence of a tailored image database and explainable AI models. Thus, the purpose of this study was to develop...

Повний опис

Бібліографічні деталі
Автори: Michiko Yonehara, Yuji Nakagawa, Yuji Ayatsuka, Yuko Hara, Jun Shoji, Nobuyuki Ebihara, Takenori Inomata, Tianxiang Huang, Ken Nagino, Ken Fukuda, Tatsuma Kishimoto, Tamaki Sumi, Atsuki Fukushima, Hiroshi Fujishima, Moeko Kawai, Etsuko Takamura, Eiichi Uchio, Kenichi Namba, Ayumi Koyama, Tomoko Haruki, Shin-ich Sasaki, Yumiko Shimizu, Dai Miyazaki
Формат: Стаття
Мова:English
Опубліковано: Elsevier 2025-01-01
Серія:Allergology International
Предмети:
Allergic conjunctivitis
Artificial intelligence
Atopic keratoconjunctivitis
Deep learning
Vernal keratoconjunctivitis
Онлайн доступ:http://www.sciencedirect.com/science/article/pii/S1323893024000777

Інтернет

http://www.sciencedirect.com/science/article/pii/S1323893024000777

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