Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example
Bowness, James S Liu, Xiaoxuan Keane, Pearse A
Bowness, James S
Liu, Xiaoxuan
Keane, Pearse A
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2024-02-01
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Abstract
A recent study by Suissa and colleagues explored the clinical relevance of a medical image segmentation metric (Dice metric) commonly used in the field of artificial intelligence (AI). They showed that pixel-wise agreement for physician identification of structures on ultrasound images is variable, and a relatively low Dice metric (0.34) correlated to a substantial agreement on subjective clinical assessment. We highlight the need to bring structure and clinical perspective to the evaluation of medical AI, which clinicians are best placed to direct.
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Bowness JS, Liu X, Keane PA. Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example. Br J Anaesth. 2024 May;132(5):1016-1021. doi: 10.1016/j.bja.2023.12.024.
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