医学
工作流程
瘢痕疙瘩
集合(抽象数据类型)
领域(数学)
人工智能
数据科学
计算机科学
病理
数据库
数学
纯数学
程序设计语言
作者
Jingyang Zhou,Renjie Cui,Lin Lin
标识
DOI:10.1097/scs.0000000000011259
摘要
Aberrant skin healing after trauma sometimes causes substantial physical and psychological problems for patients with keloid. Therefore, it is particularly important to understand the pathogenic process, find additional risk factors, investigate novel, comprehensive, and accurate therapeutic options, and set up an efficient workflow for accurate prognostic prediction of keloid. Artificial intelligence technology, which has made significant strides in recent years, maybe a good option for achieving the aforementioned objectives. On the basis of actual clinical big data, it can perform sufficiently thorough data mining and quickly and accurately anticipate diseases, providing us with new ideas and insights for the keloid. This article seeks to do a thorough analysis of the recently published literature that looks at the application of artificial intelligence in keloid holistically to serve as a reference and inspiration for future research in this field.
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