医学
系统回顾
观察研究
梅德林
医疗保健
概念证明
临床实习
循证医学
人工智能
重症监护医学
计算机科学
替代医学
护理部
病理
操作系统
经济
经济增长
法学
政治学
作者
Francisco Serra E Moura,Kavit Amin,Chidi Ekwobi
出处
期刊:Burns & Trauma
[Oxford University Press]
日期:2021-01-01
卷期号:9
被引量:15
标识
DOI:10.1093/burnst/tkab022
摘要
Artificial intelligence (AI) is an innovative field with potential for improving burn care. This article provides an updated review on machine learning in burn care and discusses future challenges and the role of healthcare professionals in the successful implementation of AI technologies.A systematic search was carried out on MEDLINE, Embase and PubMed databases for English-language articles studying machine learning in burns. Articles were reviewed quantitatively and qualitatively for clinical applications, key features, algorithms, outcomes and validation methods.A total of 46 observational studies were included for review. Assessment of burn depth (n = 26), support vector machines (n = 19) and 10-fold cross-validation (n = 11) were the most common application, algorithm and validation tool used, respectively.AI should be incorporated into clinical practice as an adjunct to the experienced burns provider once direct comparative analysis to current gold standards outlining its benefits and risks have been studied. Future considerations must include the development of a burn-specific common framework. Authors should use common validation tools to allow for effective comparisons. Level I/II evidence is required to produce robust proof about clinical and economic impacts.
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