[基于对父母语言的计算分析来检测自闭症]
Maria Eleonora Minissi1, Alberto Altozano1, Lucia Gómez-Zaragozá1
1Laboratorio de Neurotecnologías Inmersivas. Instituto Human-Tech. Universidad Politécnica de Valencia, España.
Medicina
|February 16, 2026
概括
这项研究使用人工智能分析家长的语音,以检测早期自闭症谱系障碍 (ASD),达到84%的准确性. 这种方法可以改善查,减少诊断和干预的等待时间.
科学领域:
- 发育儿科 发育儿科
- 计算语言学 计算语言学
- 医疗保健中的人工智能
背景情况:
- 早期发现自闭症谱系障碍 (ASD) 是至关重要的,但受到有限资源的挑战.
- 父母的叙述提供了对儿童发展的宝贵见解,但很难系统地分析.
- 现有的ASD诊断护理途径往往是紧张的,导致干预的延迟.
研究的目的:
- 调查自动分析护理人员对ASD检测的开放式反应的潜力.
- 利用家长的语音数据开发一种用于识别儿童ASD的计算方法.
- 评估支持自闭症查,优先级和转诊过程的可行性.
主要方法:
- 一项研究分析了护理人员对来自51个家庭的12个ADI-R启发问题 (25个自闭症,26个对照) 的反应.
- 开放式的文本响应被使用OpenAI的text-ada-embedding-large-v3.3转换成语义表示.
- 机器学习模型被训练每一个问题,纳入问题文本,并通过多数投票汇总进行分类.
主要成果:
- 最好的分类策略在检测ASD时实现了84%的准确性和ROC-AUC为1.0.
- 对家长语音的计算分析表明,识别自闭症有很大的潜力.
- 这些发现表明,自动自动检测自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自在线自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动自动
结论:
- 父母语音的自动化分析显示,ASD早期检测具有前途,可能有助于临床决策.
- 这项试点研究强调了减少职业负担和改善及时获得干预的可能性.
- 需要进一步的研究来解决局限性问题,并确保负责任的临床翻译,考虑到伦理方面的影响.
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