Application of Explainable Artificial Intelligence in Detecting Foot Characteristics: An Exploratory Study Focused on Sex Differences
Background: Foot morphologies related to specific populations and diseases have been reported; however, their identification remains limited by human cognition. This study aimed to evaluate the utility of explainable artificial intelligence (XAI) in detecting foot characteristics, using sex differences as an exploratory study.
Authors
- Kenta Makabe (ORCID: https://orcid.org/0000-0003-4021-3740)
- Yasunori Omata (ORCID: https://orcid.org/0000-0002-8912-7483)
- Ryutaro Takeda (ORCID: https://orcid.org/0000-0003-4134-9519)
- Toshiko Iidaka
- Taro Kasai (ORCID: https://orcid.org/0000-0002-5523-1602)
- T Matsumoto
- S Shinichi TANAKA
- Noriko Yoshimura
Institutions
- Jichi Medical University (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Journal of Orthopaedic Foot and Ankle Science
- Published
- 2026-07-26
- DOI
- https://doi.org/10.64079/jofas.2025-0020
- Primary Topic
- Explainable Artificial Intelligence (XAI)
- Type
- article
- Field-Weighted Citation Impact
- 0.00