Automatic Identification of High-Risk Autism Spectrum Disorder: A Feasibility Study Using Video and Audio Data Under the Still-Face Paradigm-Reference-Cited by-同舟云学术

Automatic Identification of High-Risk Autism Spectrum Disorder: A Feasibility Study Using Video and Audio Data Under the Still-Face Paradigm

Published:2020-11 Issue:11 Volume:28 Page:2401-2410
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Tang Chuangao^ORCID,Zheng Wenming^ORCID,Zong Yuan^ORCID,Qiu Nana,Lu Cheng^ORCID,Zhang Xilei,Ke Xiaoyan,Guan Cuntai^ORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Jiangsu Frontier Technology Basic Research Project

Postgraduate Research and Practice Innovation Program of Jiangsu Province

Postdoctoral Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Effective Machine Learning Model to Detect and Analyze the Autism Spectrum Disorder;2024 International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS);2024-04-17