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基于AI的算法的诊断性能,使用MRI特征来区分NMOSD和MS:系统性审查和元分析

Masoud Etemadifar¹, Mahdi Norouzi¹, Seyyed-Ali Alaei¹

¹School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Multiple sclerosis and related disorders

|May 23, 2024

概括

人工智能 (AI) 模型在使用MRI扫描来区分神经omyelitis光学谱系障碍 (NMOSD) 和多发性硬化症 (MS) 方面表现有前途. 为了优化诊断准确度,需要使用标准化协议进行进一步的研究.

科学领域:

神经成像是一种神经成像.
人工智能的人工智能
神经学神经学

背景情况:

区分神经omyelitis光学谱障碍 (NMOSD) 和多发性硬化症 (MS) 对于有效治疗至关重要,因为它们的MRI特征可能会重叠.
显著的MRI损伤模式,如U纤维和道森的手指类型病变 (MS) 与线性表皮病变 (NMOSD),有助于诊断.
人工智能 (AI) 越来越多地用于分析复杂的MRI数据,以改善诊断歧视.

结论:

利用MRI特征的人工智能模型表明,在NMOSD和MS之间进行区分有很大的潜力.
图像协议,模型评估和报告指标的异质性目前影响着人工智能驱动歧视的可靠性.
未来的研究应该优先考虑多中心数据集,标准化协议和透明的报告,以提高AI诊断工具的性能和可靠性.

关键词:

在这里,我们可以看到AIAIAI.人工智能的人工智能在MSMSMSMSMSMSMSMSMSMSMS中,我们可以看到磁共振成像是一种磁共振成像技术.多发性硬化症是多发性硬化症.这是NMOSD的NMOSD.

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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...