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使用脑成像进行帕金森病诊断和预后的机器学习模型:一般概述,主要挑战和未来方向

Beatriz Garcia Santa Cruz¹, Andreas Husch², Frank Hertel¹

¹National Department of Neurosurgery, Centre Hospitalier de Luxembourg, Luxembourg, Luxembourg.

Frontiers in aging neuroscience

|August 4, 2023

概括

这篇评论探讨了机器学习 (ML) 如何使用MRI扫描来诊断帕金森病 (PD). 它强调了ML的潜力,同时解决了安全临床使用的挑战.

科学领域:

神经成像是一种神经成像.
人工智能在医学中的应用

背景情况:

帕金森病 (PD) 是一种进展性神经退行性疾病,影响运动和认知功能,需要早期诊断和预后.
磁共振成像 (MRI) 对于理解PD的大脑表现和开发诊断支持系统至关重要.

研究的目的:

审查最新的机器学习 (ML) 技术,以使用脑MRI进行帕金森病 (PD) 自动诊断和预后.
分析将ML应用于医学诊断的挑战,特别是对于PD,并讨论临床整合的局限性.

主要方法:

在脑MRI中应用到PD诊断和预后的ML技术的全面审查.
在疾病特异性,任务特异性和技术特异性层面分析挑战.

主要成果:

机器学习 (ML) 和深度学习 (DL) 在PD的高维神经成像数据中揭示了复杂的模式.
确定了阻碍基于ML的PD诊断工具安全临床转化的主要挑战.

结论:

通过脑MRI分析,ML为改善PD诊断和预后提供了显著的潜力.
解决已确定的挑战对于将ML安全有效地纳入帕金森病的临床实践至关重要.

关键词:

帕金森病的疾病.计算机辅助诊断是指计算机辅助的诊断.深度学习是一种深度学习.数字健康数字健康机器学习是机器学习.神经成像是一种神经成像.翻译 ML 的 ML

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