医学诊断
医学实验室
背景(考古学)
计算机科学
自动化
精密医学
人工智能
个性化医疗
过程(计算)
临床诊断
医学物理学
数据科学
医学
工程类
重症监护医学
病理
生物信息学
操作系统
生物
古生物学
机械工程
作者
Heying Xie,Yin Jia,Shanrong Liu
标识
DOI:10.1002/inmd.20230056
摘要
Abstract Artificial intelligence (AI)‐driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.
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