Narrative review highlights links between fatigue and diagnostic accuracy in radiologists, suggesting AI may aid decision-making.
The radiology reading room today is busier than ever with increasing numbers of cases that contain more images, sequences, and complex findings. Consequently, radiologists are becoming more fatigued and burned out. To address this growing problem, studies have been conducted to objectively measure fatigue and its impact on diagnostic accuracy and efficiency, with growing evidence that the impact is negative and significant after just 8 h of clinical work. The impact (increased errors, reduced ability to focus) may be greater for residents than for experienced radiologists. Artificial intelligence (AI) may be a potential solution to address fatigue, but we need to understand exactly how it affects users and their decision-making processes to optimally use it as a decision aid in clinical practice.
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E. A. Krupinski (2025) studied this question.
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