Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example
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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.Citation
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.Type
OtherPMID
38302346Journal
British Journal of AnaesthesiaPublisher
Elsevierae974a485f413a2113503eed53cd6c53
10.1016/j.bja.2023.12.024