基于MRI的结构和/或功能机器学习技术用于注意力缺陷/多动障碍诊断:系统性审查和元分析
Lu Tian1, Helin Zheng1, Ke Zhang1
1Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing 400014, China.
Journal of affective disorders
|April 5, 2024
概括
使用结构性MRI (sMRI) 或功能性MRI (fMRI) 的机器学习 (ML) 技术在诊断ADHD方面表现有前途. 这些方法为ADHD诊断提供了一种有价值的客观方法.
科学领域:
- 神经成像是一种神经成像.
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 注意缺陷/多动障碍 (ADHD) 的诊断依赖于主观的标准.
- 需要客观的诊断方法来改善ADHD评估.
- 机器学习 (ML) 应用于神经成像数据提供了一个潜在的解决方案.
结论:
- 基于sMRI或fMRI的ML技术为ADHD提供了一个有希望的客观诊断方法.
- 对包括EEG在内的多式联络数据进行进一步的研究是全面基于ML的ADHD诊断的必要条件.
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