机器学习技术在颅内出血ct诊断和分类中的应用

Q4 Medicine

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko Pub Date : 2023-01-01 DOI:10.17116/neiro20238702185

A K Smorchkova, A N Khoruzhaya, E I Kremneva, A V Petryaikin

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引用次数: 0

摘要

本文综述了机器学习技术在基于ct的颅内出血诊断中的创造、实施和有效性的经验。作者分析了2015年至2022年间的21篇原创文章，使用了以下关键词:“颅内出血”、“机器学习”、“深度学习”、“人工智能”。该综述包含关于机器学习基本概念的一般数据，并更详细地考虑了用于为某些类型的临床任务创建人工智能算法的数据集的技术特征，它们对有效性和临床经验的可能影响等方面。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

[Machine learning technologies in CT-based diagnostics and classification of intracranial hemorrhages].

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.

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来源期刊

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko Medicine-Neurology (clinical)

CiteScore

0.70

自引率

0.00%

发文量

期刊介绍： Scientific and practical peer-reviewed journal. This publication covers the theoretical, practical and organizational problems of modern neurosurgery, the latest advances in the treatment of various diseases of the central and peripheral nervous system. Founded in 1937. English version of the journal translates from Russian version since #1/2013.