Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example

被引:1
|
作者
Bowness, James S. [1 ,2 ]
Liu, Xiaoxuan [3 ,4 ]
Keane, Pearse A. [5 ,6 ]
机构
[1] Univ Oxford, Nuffield Dept Clin Anaesthesia, Oxford, England
[2] Aneurin Bevan Univ Hlth Board, Dept Anaesthesia, Newport, Wales
[3] Univ Hosp Birmingham NHS Fdn Trust, Birmingham, England
[4] Univ Birmingham, Coll Med & Dent Sci, Birmingham, England
[5] UCL, Inst Ophthalmol, Fac Brain Sci, London, England
[6] Moorfields Eye Hosp NHS Fdn Trust, NIHR Biomed Res Ctr, London, England
关键词
artificial intelligence; regional anaesthesia; ultrasound; evaluation; medical devices; regulation; standardisation; AMERICAN SOCIETY; PAIN MEDICINE; EDUCATION;
D O I
10.1016/j.bja.2023.12.024
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
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.
引用
收藏
页码:1016 / 1021
页数:6
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