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Updated: Sep 9, 2025

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
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ASD-HybridNet:用于检测自闭症谱系障碍的混合深度学习框架

Nirmal Rai1, P C Pradhan1, Hemanta Saikia2

  • 1Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim Manipal University, 737136, Sikkim, India.

Magnetic resonance imaging
|August 28, 2025
PubMed
概括

本研究介绍了ASD-HybridNet,这是一种使用fMRI数据检测自闭症谱系障碍 (ASD) 的新型深度学习方法. 该方法通过结合感兴趣的区域和功能连接信息来提高诊断的准确性.

关键词:
自闭症进行分类深度学习机器学习功能磁共振成像

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Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
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Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
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