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对2020年至2022年使用胸部CT进行COVID-19查的深度结构化学习进行系统审查

K C Santosh¹, Debasmita GhoshRoy², Suprim Nakarmi³

¹2AI: Applied Artificial Intelligence Research Lab, Vermillion, SD 57069, USA.

Healthcare (Basel, Switzerland)

|September 9, 2023

概括

人工智能 (AI) 和深度学习在分析胸部CT扫描以检测COVID-19方面表现有前途. 需要进一步的研究来克服跨人群模型培训和临床应用数据集可变性方面的挑战.

科学领域:

医疗成像医学成像
人工智能的人工智能
传染性疾病传染性疾病

背景情况:

由于COVID-19的流行,诊断工具的快速发展成为必要.
人工智能 (AI) 在医学成像分析中为疾病检测提供了潜在的好处.
胸部CT扫描对于诊断COVID-19至关重要,但解释可能具有挑战性.

研究的目的:

通过2020-2022年的胸部CT数据,审查用于COVID-19分析的AI驱动的方法.
评估深度学习算法在COVID-19查和决策中的有效性.
在基于AI的COVID-19检测中识别挑战和新兴技术.

主要方法:

2020年至2022年间发表的231篇同行评审研究文章的系统审查.
使用PubMed Central和Web of Science上的特定关键词进行元分析.
专注于AI和深度学习应用在COVID-19的胸部CT中.

主要成果:

人工智能和深度学习算法在分析COVID-19的胸部CT扫描中显示出潜力.
许多人工智能工具都是为了教育和培训目的而开发的.
挑战包括数据集大小的变化和跨人口培训/测试模型的需求.

结论:

人工智能有望通过胸部CT改善COVID-19的检测和分析.
需要进一步开发以解决广泛临床采用的局限性.
数据集的标准化和强大的验证对于可靠的AI工具至关重要.

关键词:

在 COVID-19 疫情中,胸部CT CT 胸部CT CT 胸部CT 胸部CT 深度结构化学习 (deep structured learning) 是一种深度结构化的学习.医学成像医学成像

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