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  1. 120 熱帯医学研究所 = Institute of Tropical Medicine
  2. 120 学術雑誌論文 = Articles in academic journal

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

http://hdl.handle.net/10069/0002002159
http://hdl.handle.net/10069/0002002159
81a79289-0a67-402a-afb2-9a5e6ba1a2cd
名前 / ファイル ライセンス アクション
SR15_13113.pdf SR15_13113.pdf (2.4 MB)
アイテムタイプ 学術雑誌論文 / Journal Article(1)
公開日 2025-05-08
タイトル
タイトル Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance
言語 en
言語
言語 eng
キーワード
言語 en
主題Scheme Other
主題 AMR
キーワード
言語 en
主題Scheme Other
主題 AI
キーワード
言語 en
主題Scheme Other
主題 Game theory
キーワード
言語 en
主題Scheme Other
主題 Social dilemma
キーワード
言語 en
主題Scheme Other
主題 Public health
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者 Ito, Hiromu

× Ito, Hiromu

en Ito, Hiromu

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Wada, Takayuki

× Wada, Takayuki

en Wada, Takayuki

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Ichinose, Genki

× Ichinose, Genki

en Ichinose, Genki

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Tanimoto, Jun

× Tanimoto, Jun

en Tanimoto, Jun

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Yoshimura, Jin

× Yoshimura, Jin

en Yoshimura, Jin

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Yamamoto, Taro

× Yamamoto, Taro

en Yamamoto, Taro

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Morita, Satoru

× Morita, Satoru

en Morita, Satoru

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抄録
内容記述タイプ Abstract
内容記述 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.
言語 en
書誌情報 en : Scientific Reports

巻 15, 号 1, p. art. no. 13113, 発行日 2025-04-16
出版者
出版者 Springer Nature
言語 en
ISSN
収録物識別子タイプ EISSN
収録物識別子 2045-2322
DOI
関連タイプ isIdenticalTo
識別子タイプ DOI
関連識別子 10.1038/s41598-025-95110-x
権利
権利情報 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2025
言語 en
著者版フラグ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
引用
内容記述タイプ Other
内容記述 Scientific Reports, 15(1), art. no. 13113; 2025
言語 en
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