Application of artificial intelligence in trauma orthopedics: Limitation and prospects  

作　　者：Maryam Salimi Joshua A Parry Raha Shahrokhi Seyedarad Mosalamiaghili 

机构地区：[1]Department of Orthopaedic Surgery,Denver Health Medical Center,Denver,CO 80215,United States [2]Student Research Committee,Shiraz University of Medical Sciences,Shiraz 7138433608,Iran

出　　处：《World Journal of Clinical Cases》2023年第18期4231-4240,共10页世界临床病例杂志

摘　　要：The varieties and capabilities of artificial intelligence and machine learning in orthopedic surgery are extensively expanding.One promising method is neural networks,emphasizing big data and computer-based learning systems to develop a statistical fracture-detecting model.It derives patterns and rules from outstanding amounts of data to analyze the probabilities of different outcomes using new sets of similar data.The sensitivity and specificity of machine learning in detecting fractures vary from previous studies.AI may be most promising in the diagnosis of less-obvious fractures that are more commonly missed.Future studies are necessary to develop more accurate and effective detection models that can be used clinically.

关 键 词：Artificial intelligence Machine learning ORTHOPEDICS TRAUMA Neural network 

分 类 号：R68[医药卫生—骨科学] TP18[医药卫生—外科学]