Development and Validation of Deep Learning Models for the Multiclassification of Reflux Esophagitis Based on the Los Angeles Classification.

Ge, Hailong; Zhou, Xin; Wang, Yu; Xu, Jian; Mo, Feng; Chao, Chen; Zhu, Jinzhou; Yu, Weixin

Ge, Hailong; Zhou, Xin; Wang, Yu; Xu, Jian; Mo, Feng; Chao, Chen; Zhu, Jinzhou; Yu, Weixin.

Afiliación

Ge H; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Zhou X; Department of Gastroenterology, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Wang Y; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Xu J; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Mo F; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Chao C; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.
Zhu J; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215000, China.
Yu W; Department of General Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou 213200, China.

J Healthc Eng ; 2023: 7023731, 2023.

Article en En | MEDLINE | ID: mdl-36852218

Asunto(s)

Aprendizaje Profundo; Esofagitis Péptica; Ácido Glicirretínico; Humanos; Esofagitis Péptica/diagnóstico; Los Angeles; Suministros de Energía Eléctrica

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Esofagitis Péptica / Aprendizaje Profundo / Ácido Glicirretínico Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: J Healthc Eng Año: 2023 Tipo del documento: Article País de afiliación: China

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