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Shivani Pandya1, Swati Jain1, Jaiprakash Verma1
1Department of Computer Science and Engineering, Nirma University, Ahmedabad, Gujarat 382481, India.
人工智能 (AI) 在使用各种数据类型的早期自闭症谱系障碍 (ASD) 检测方面表现有前途. 这篇评论强调了人工智能.
科学领域:
- 神经科学和计算机科学
- 发展心理学 发展心理学
- 医疗信息学 医疗信息学
背景情况:
- 自闭症谱系障碍 (ASD) 是一种复杂的神经发育状况,影响社会互动和沟通.
- 早期发现ASD对于有效干预和改善生活质量至关重要.
- 人工智能 (AI) 正在成为ASD研究和诊断的强大工具.
研究的目的:
- 为早期自闭症谱系障碍检测提供人工智能应用的全面概述.
- 在过去十年中,审查基于人工智能的自闭症分类的最新进展.
- 将ASD研究中的AI与联合国关于健康和正义的可持续发展目标保持一致.
主要方法:
- 对最近 (过去十年) 关于人工智能用于ASD分类的出版物的系统审查.
- 分析各种数据模式:眼睛的凝视,面部表情,运动技能,MRI/fMRI,EEG.
- 将其分类为行为和生物标记,包括多模式方法.
主要成果:
- 人工智能有效地利用各种数据模式来检测自闭症谱系障碍.
- 从ASD历史到当前的人工智能发展的时间表.
- 分析包括成功,挑战和公开可用的数据集,用于ASD中的AI.
结论:
- 人工智能对早期和准确的自闭症谱系障碍识别有很大的潜力.
- 在AI驱动的ASD检测方面进行进一步的研究和开发至关重要.
- 本综述为AI和ASD领域的研究人员提供了一个系统的概述.
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