End-to-End Model-Based Detection of Infants with Autism Spectrum Disorder Using a Pretrained Model.

Lee, Jung Hyuk; Lee, Geon Woo; Bong, Guiyoung; Yoo, Hee Jeong; Kim, Hong Kook

Lee, Jung Hyuk; Lee, Geon Woo; Bong, Guiyoung; Yoo, Hee Jeong; Kim, Hong Kook.

Afiliação

Lee JH; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.
Lee GW; AI Graduate School, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.
Bong G; Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea.
Yoo HJ; Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea.
Kim HK; College of Medicine, Seoul National University, Seoul 03980, Republic of Korea.

Sensors (Basel) ; 23(1)2022 Dec 25.

Article em En | MEDLINE | ID: mdl-36616801

Assuntos

Transtorno do Espectro Autista; Criança; Humanos; Lactente; Transtorno do Espectro Autista/diagnóstico; Memória de Longo Prazo; Gravação em Vídeo/métodos

Palavras-chave

autism spectrum disorder; autoencoder; bidirectional long short-term memory (BLSTM); end-to-end neural network; joint optimization; pretrained model

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transtorno do Espectro Autista Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Child / Humans / Infant Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article

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