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Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation.
Xia, Tai-Hui; Tan, Man; Li, Jing-Hua; Wang, Jing-Jing; Wu, Qing-Qing; Kong, De-Xing.
Afiliación
  • Xia TH; Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
  • Tan M; The School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
  • Li JH; Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
  • Wang JJ; Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
  • Wu QQ; Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
  • Kong DX; The School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Chin Med J (Engl) ; 134(15): 1828-1837, 2021 Jul 01.
Article en En | MEDLINE | ID: mdl-34224403
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Female / Humans / Infant / Newborn / Pregnancy Idioma: En Revista: Chin Med J (Engl) Año: 2021 Tipo del documento: Article País de afiliación: China
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Female / Humans / Infant / Newborn / Pregnancy Idioma: En Revista: Chin Med J (Engl) Año: 2021 Tipo del documento: Article País de afiliación: China