Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance

Hiromu Ito, Takayuki Wada, Genki Ichinose, Jun Tanimoto, Jin Yoshimura, Taro Yamamoto, Satoru Morita

研究成果: ジャーナルへの寄稿学術誌査読

抄録

Currently, antimicrobial resistance (AMR) poses a major public health challenge. The emergence of AMR, which significantly threatens public health, is primarily due to the overuse of antimicrobial agents. This study explored the possibility that the ethical dilemmas inherent in the context of AMR may hinder the adoption of diagnostic artificial intelligence (AI). We conducted a web survey across eight countries/areas to assess public preference between two hypothetical AI types: one prioritizing individual health and the other considering the global AMR threat. Our results revealed a societal preference for the utilization of both AI types, reflecting a conflict between recognizing the significance of AMR and the desire for individualized treatment. Interestingly, the survey indicated significant gender and age differences in AI preferences, and the majority of respondents opposed the idea of AI standardization in treatment. These findings highlight the challenges of incorporating AI into public health and the necessity of considering public sentiment in addressing global health issues such as AMR.

本文言語英語
論文番号13113
ジャーナルScientific reports
15
1
DOI
出版ステータス出版済み - 12月 2025

!!!All Science Journal Classification (ASJC) codes

  • 一般

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