Key result
AI-ECG algorithms show potential to improve diagnosis and risk stratification by addressing clinician literacy limitations.
Why the study?
ECG clinical utility depends on accurate interpretation, but waning clinician ECG literacy and widespread reliance on computer analysis present challenges alongside emerging AI-ECG advances.
This review highlights the clinical utility of ECGs, challenges in interpretation and education, and the emerging role of AI-augmented ECG algorithms.
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May aid ECG interpretation amid declining clinician literacy; leaves open prospective validation before clinical adoption.
Rafie et al. (2021) conducted a review in ECG interpretation. Artificial intelligence-augmented ECG (AI-ECG) was evaluated. Artificial intelligence-augmented ECG (AI-ECG) algorithms demonstrate the potential to risk stratify, diagnose, and interpret ECGs, addressing current limitations in clinician ECG literacy.
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