A deep learning model adjusting for infant gender, age, height, and weight to determine whether the individual infant suit ultrasound examination of developmental dysplasia of the hip (DDH).

Chen, Xiaoyi; Zhang, Shuangshuang; Shi, Wei; Wu, Dechao; Huang, Bingxuan; Tao, Hongwei; He, Xuezhi; Xu, Na

Chen, Xiaoyi; Zhang, Shuangshuang; Shi, Wei; Wu, Dechao; Huang, Bingxuan; Tao, Hongwei; He, Xuezhi; Xu, Na.

Afiliación

Chen X; Department of Ultrasound, Shenzhen Children's Hospital of China Medical University, Shenzhen, China.
Zhang S; Department of Ultrasound, Shenzhen Children's Hospital of China Medical University, Shenzhen, China.
Shi W; Department of Orthopedics, Shenzhen Pediatrics Institute of Shantou University Medical College, Shenzhen, China.
Wu D; Department of Orthopedics, Shenzhen Pediatrics Institute of Shantou University Medical College, Shenzhen, China.
Huang B; Department of Ultrasound, Shenzhen Pediatrics Institute of Shantou University Medical College, Shenzhen, China.
Tao H; Department of Ultrasound, Shenzhen Pediatrics Institute of Shantou University Medical College, Shenzhen, China.
He X; Department of Ultrasound, Shenzhen Pediatrics Institute of Shantou University Medical College, Shenzhen, China.
Xu N; Department of Ultrasound, Shenzhen Children's Hospital of China Medical University, Shenzhen, China.

Front Pediatr ; 11: 1293320, 2023.

Article en En | MEDLINE | ID: mdl-38046675

Palabras clave

deep learning; developmental dysplasia of the hip; individuation; infant; ultrasonography

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Pediatr Año: 2023 Tipo del documento: Article País de afiliación: China

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