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Guidelines or consensus statements on the use of artificial intelligence for medicine: a systematic review
Ying Wang;
Nian Li;
Lingmin Chen;
Miaomiao Wu;
Sha Meng;
Zelei Dai;
Yonggang Zhang;
Mike Clarke
ABSTRACT
Background:
The application of AI in the delivery of health care is a promising area, guidelines or consensus statements on AI on various topics have been developed.
Objective:
We performed the current study to assess the quality of guidelines in the field of AI for clinical practice and to provide the foundation for recommendations about the future development of AI guidelines.
Methods:
We searched seven electronic databases from inception through 6 April 2022, screened the AI guidelines and consensus statements for eligibility. The AGREE II and RIGHT tools assessed the methodological and reporting quality of the included articles.
Results:
Ten guidelines and eleven consensus statements published between 2019 and 2022 were included in this systematic review, their content involved disease screening and diagnosis, reporting of AI trials, AI image, AI data. Our quality assessment revealed that the average overall scores on AGREE II ranged from 3 to 5.5 on a 7-point Likert scale and the mean overall reporting rate of RIGHT was 49.7%, ranging from 37.1% to 77.1%.
Conclusions:
The result indicated important differences in the quality of the different AI guidelines. We made recommendations for their methodological and reporting quality.
Citation
Please cite as:
Wang Y, Li N, Chen L, Wu M, Meng S, Dai Z, Zhang Y, Clarke M
Guidelines, Consensus Statements, and Standards for the Use of Artificial Intelligence in Medicine: Systematic Review