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

Journal: Allergology international : official journal of the Japanese Society of Allergology
Published Date: Aug 17, 2024

Abstract

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 an explainable AI model that can not only diagnose ACDs but also present the basis for the diagnosis.

Authors

  • Michiko Yonehara
    Division of Ophthalmology and Visual Science, Faculty of Medicine, Tottori University, Tottori, Japan.
  • Yuji Nakagawa
    Technology Laboratory, CRESCO LTD., Tokyo, Japan.
  • Yuji Ayatsuka
    Cresco Ltd, Technology Laboratory, Tokyo, Japan.
  • Yuko Hara
    Department of Ophthalmology, Ehime University Graduate School of Medicine, Ehime, Japan.
  • Jun Shoji
    Division of Ophthalmology, Department of Visual Sciences, Nihon University School of Medicine, Tokyo, Japan.
  • Nobuyuki Ebihara
    Department of Ophthalmology, Juntendo University Urayasu Hospital, Chiba, Japan.
  • Takenori Inomata
    Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan.
  • Tianxiang Huang
    Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
  • Ken Nagino
    Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan; Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan.
  • Ken Fukuda
    Department of Ophthalmology, Kochi Medical School, Kochi University, Kochi, Japan.
  • Tatsuma Kishimoto
    Department of Ophthalmology, Kochi Medical School, Kochi University, Kochi, Japan.
  • Tamaki Sumi
    Department of Ophthalmology, Kochi Medical School, Kochi University, Kochi, Japan.
  • Atsuki Fukushima
    Department of Ophthalmology, Tsukazaki Hospital, Hyogo, Japan.
  • Hiroshi Fujishima
    Department of Ophthalmology, School of Dental Medicine, Tsurumi University, Kanagawa, Japan.
  • Moeko Kawai
  • Etsuko Takamura
    Department of Ophthalmology, School of Medicine, Tokyo Women's Medical University, Tokyo, Japan.
  • Eiichi Uchio
    Department of Ophthalmology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan.
  • Kenichi Namba
    Department of Ophthalmology, Faculty of Medicine, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Ayumi Koyama
    Department of Ophthalmology, Tottori University, 36-1 Nishicho, Yonago, Tottori, 683-8504, Japan.
  • Tomoko Haruki
    Division of Ophthalmology and Visual Science, Faculty of Medicine, Tottori University, Tottori, Japan.
  • Shin-Ich Sasaki
    Division of Ophthalmology and Visual Science, Faculty of Medicine, Tottori University, Tottori, Japan.
  • Yumiko Shimizu
    Department of Ophthalmology, Tottori University, 36-1 Nishicho, Yonago, Tottori, 683-8504, Japan.
  • Dai Miyazaki
    Department of Ophthalmology, Tottori University, 36-1 Nishicho, Yonago, Tottori, 683-8504, Japan. miyazaki-ttr@umin.ac.jp.

Keywords

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