Smorchkova A K, Khoruzhaya A N, Kremneva E I, Petryaikin A V
Moscow Research Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow, Russia.
Neurology Research Center, Moscow, Russia.
Zh Vopr Neirokhir Im N N Burdenko. 2023;87(2):85-91. doi: 10.17116/neiro20238702185.
This review discusses pooled experience of creation, implementation and effectiveness of machine learning technologies in CT-based diagnosis of intracranial hemorrhages. The authors analyzed 21 original articles between 2015 and 2022 using the following keywords: «intracranial hemorrhage», «machine learning», «deep learning», «artificial intelligence». The review contains general data on basic concepts of machine learning and also considers in more detail such aspects as technical characteristics of data sets used for creation of AI algorithms for certain type of clinical task, their possible impact on effectiveness and clinical experience.
本综述讨论了机器学习技术在基于CT的颅内出血诊断中的创建、实施及有效性的综合经验。作者使用以下关键词分析了2015年至2022年间的21篇原创文章:“颅内出血”、“机器学习”、“深度学习”、“人工智能”。该综述包含了机器学习基本概念的一般数据,并更详细地考虑了诸如用于特定类型临床任务的人工智能算法创建的数据集的技术特征、它们对有效性的可能影响以及临床经验等方面。