論文

国際誌
2021年2月21日

Efficacy of Artificial-Intelligence-Driven Differential-Diagnosis List on the Diagnostic Accuracy of Physicians: An Open-Label Randomized Controlled Study.

International journal of environmental research and public health
  • Yukinori Harada
  • ,
  • Shinichi Katsukura
  • ,
  • Ren Kawamura
  • ,
  • Taro Shimizu

18
4
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/ijerph18042086

BACKGROUND: The efficacy of artificial intelligence (AI)-driven automated medical-history-taking systems with AI-driven differential-diagnosis lists on physicians' diagnostic accuracy was shown. However, considering the negative effects of AI-driven differential-diagnosis lists such as omission (physicians reject a correct diagnosis suggested by AI) and commission (physicians accept an incorrect diagnosis suggested by AI) errors, the efficacy of AI-driven automated medical-history-taking systems without AI-driven differential-diagnosis lists on physicians' diagnostic accuracy should be evaluated. OBJECTIVE: The present study was conducted to evaluate the efficacy of AI-driven automated medical-history-taking systems with or without AI-driven differential-diagnosis lists on physicians' diagnostic accuracy. METHODS: This randomized controlled study was conducted in January 2021 and included 22 physicians working at a university hospital. Participants were required to read 16 clinical vignettes in which the AI-driven medical history of real patients generated up to three differential diagnoses per case. Participants were divided into two groups: with and without an AI-driven differential-diagnosis list. RESULTS: There was no significant difference in diagnostic accuracy between the two groups (57.4% vs. 56.3%, respectively; p = 0.91). Vignettes that included a correct diagnosis in the AI-generated list showed the greatest positive effect on physicians' diagnostic accuracy (adjusted odds ratio 7.68; 95% CI 4.68-12.58; p < 0.001). In the group with AI-driven differential-diagnosis lists, 15.9% of diagnoses were omission errors and 14.8% were commission errors. CONCLUSIONS: Physicians' diagnostic accuracy using AI-driven automated medical history did not differ between the groups with and without AI-driven differential-diagnosis lists.

リンク情報
DOI
https://doi.org/10.3390/ijerph18042086
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/33669930
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924871
ID情報
  • DOI : 10.3390/ijerph18042086
  • PubMed ID : 33669930
  • PubMed Central 記事ID : PMC7924871

エクスポート
BibTeX RIS