Deep learning identifies cardiac coupling between mother and fetus during gestation.

Alkhodari, Mohanad; Widatalla, Namareq; Wahbah, Maisam; Al Sakaji, Raghad; Funamoto, Kiyoe; Krishnan, Anita; Kimura, Yoshitaka; Khandoker, Ahsan H

Alkhodari, Mohanad; Widatalla, Namareq; Wahbah, Maisam; Al Sakaji, Raghad; Funamoto, Kiyoe; Krishnan, Anita; Kimura, Yoshitaka; Khandoker, Ahsan H.

Afiliação

Alkhodari M; Department of Biomedical Engineering, Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, United Arab Emirates.
Widatalla N; Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
Wahbah M; Department of Biomedical Engineering, Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, United Arab Emirates.
Al Sakaji R; Department of Biomedical Engineering, Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, United Arab Emirates.
Funamoto K; Department of Biomedical Engineering, Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, United Arab Emirates.
Krishnan A; Division of Cardiology, Children's National Hospital, Washington, DC, United States.
Kimura Y; Department of Maternal and Child Health Care Medical Science, Tohoku University Graduate School of Medicine, Sendai, Japan.
Khandoker AH; Department of Biomedical Engineering, Healthcare Engineering Innovation Center, Khalifa University, Abu Dhabi, United Arab Emirates.

Front Cardiovasc Med ; 9: 926965, 2022.

Article em En | MEDLINE | ID: mdl-35966548

Palavras-chave

deep learning; electrocardiography; fetal cardiology; maternal-fetal coupling; phase coherence

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Idioma: En Revista: Front Cardiovasc Med Ano de publicação: 2022 Tipo de documento: Article

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