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English(EN) Temporal Generalization in fNIRS-Based Autism Classification: A Cross-Time-Window Transfer Benchmark

基于fNIRS的自闭症分类的时间泛化基准测试

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新发表在arXiv上的研究论文探讨了使用功能性近红外光谱（fNIRS）进行自闭症谱系障碍（ASD）分类的挑战。该研究引入了一个跨时间窗口迁移基准，以解决因受试者之间最佳观察窗口变化导致的性能下降问题。研究结果表明，虽然零样本分类准确率较低，但进行最少的受试者特定微调可显著提高结果，突显了受试者间变异性是主要障碍。研究还证明了域对抗和自监督策略在无需目标受试者数据的情况下实现稳健分类的有效性，表明可以从短fNIRS窗口中提取相关信息。 AI

排序理由 学术论文发表在arXiv上，详细介绍了基于fNIRS的自闭症分类新基准。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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基于fNIRS的自闭症分类的时间泛化基准测试

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学术论文发表在arXiv上，详细介绍了基于fNIRS的自闭症分类新基准。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Marios Petrov, Sahana Vinayak, Targol Bakhtiarvand, Moses Smith Guddah, Adham Atyabi, Frederick Shic, Kevin A. Pelphrey ·

    fNIRS 辅助自闭症分类中的时间泛化：跨时间窗口迁移基准

    arXiv:2608.07567v1 Announce Type: cross Abstract: Functional near-infrared spectroscopy (fNIRS) is a promising modality for autism spectrum disorder (ASD) classification, yet existing approaches assume temporally aligned evaluation. In practice, the optimal observation window var…

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