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Application of Explainable Artificial Intelligence in Detecting Foot Characteristics: An Exploratory Study Focused on Sex Differences

Year: 2026

Type: article

Abstract: 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.

Source: Journal of Orthopaedic Foot and Ankle Science

DOI: 10.64079/jofas.2025-0020

Authors: Taro Kasai, Ryutaro Takeda, Toshiko Iidaka, Kenta Makabe, Yasunori Omata, Noriko Yoshimura, Sakae Tanaka, Takumi Matsumoto

Institutions: The University of Tokyo, Jichi Medical University

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W7171294530

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