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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-04-16
DOI
https://doi.org/10.1038/s41598-025-95110-x
Citations
2
Primary Topic
Vaccine Coverage and Hesitancy
Type
article
Field-Weighted Citation Impact
4.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jin Yoshimura, Hiromu Ito, Satoru Morita, Jun Tanimoto et al.
2 citations
Scientific Reports
Vaccine Coverage and Hesitancy
4.33
article

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

Jin Yoshimura, Hiromu Ito, Satoru Morita, Jun Tanimoto, Genki Ichinose, Takayuki Wada, Taro Yamamoto
article en
2 citations

Abstract

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.

Scientific ReportsVol. 15(1)
Shizuoka University (JP), Kyushu University (JP), Chiba University (JP), Nagasaki University (JP), Osaka Metropolitan University (JP), Osaka International University (JP), Tokyo Metropolitan University (JP)
Japan Society for the Promotion of Science
Gender equality
Openalex Percentile: Top 8%
Vaccine Coverage and Hesitancy
4.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.