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April 8, 2020npj Digital Medicine164 citationsOpen Access

Artificial intelligence for the diagnosis of heart failure

DCDong‐Ju ChoiJPJin Joo ParkTATaqdir Ali

Structured PICO

Does an AI-CDSS improve diagnostic accuracy for heart failure in patients presenting with dyspnea compared to non-heart failure specialists?

P
Population
Retrospective cohort (n=598) and a prospective clinical pilot study of 97 patients presenting with dyspnea to the outpatient clinic (44% had heart failure).
I
Intervention
Artificial intelligence clinical decision support system (AI-CDSS)
C
Comparator
Non-heart failure specialists (using heart failure specialists as the reference standard)
O
Outcome
Concordance rate with heart failure specialists for the diagnosis of heart failure

An AI clinical decision support system demonstrated high diagnostic accuracy for heart failure, significantly outperforming non-heart failure specialists.

Abstract

= 598). A prospective clinical pilot study of 97 patients with dyspnea was used to assess the diagnostic accuracy of AI-CDSS compared with that of non-heart failure specialists. The concordance rate between AI-CDSS and heart failure specialists was evaluated. In retrospective cohort, the concordance rate was 98.3% in the test dataset. The concordance rate for patients with heart failure with reduced ejection fraction, heart failure with mid-range ejection fraction, heart failure with preserved ejection fraction, and no heart failure was 100%, 100%, 99.6%, and 91.7%, respectively. In a prospective pilot study of 97 patients presenting with dyspnea to the outpatient clinic, 44% had heart failure. The concordance rate between AI-CDSS and heart failure specialists was 98%, whereas that between non-heart failure specialists and heart failure specialists was 76%. In conclusion, AI-CDSS showed a high diagnostic accuracy for heart failure. Therefore, AI-CDSS may be useful for the diagnosis of heart failure, especially when heart failure specialists are not available.

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Cite This Study

Choi et al. (2020) studied this question.

synapsesocial.com/papers/69fd29a530a474415f89e1dchttps://doi.org/10.1038/s41746-020-0261-3
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