Efficacy of an artificial neural network algorithm based on thick-slab magnetic resonance cholangiopancreatography images for the automated diagnosis of common bile duct stones.

Hou, Jong-Uk; Park, Se Woo; Park, Seon Mee; Park, Da Hae; Park, Chan Hyuk; Min, Seonjeong

Hou, Jong-Uk; Park, Se Woo; Park, Seon Mee; Park, Da Hae; Park, Chan Hyuk; Min, Seonjeong.

Afiliación

Hou JU; School of Software, Hallym University, Chuncheon, Korea.
Park SW; Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Gyeonggi-do, Korea.
Park SM; Department of Internal Medicine, Chungbuk National University College of Medicine, Cheongju, Korea.
Park DH; Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Gyeonggi-do, Korea.
Park CH; Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea.
Min S; Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Gyeonggi-do, Korea.

J Gastroenterol Hepatol ; 36(12): 3532-3540, 2021 Dec.

Article en En | MEDLINE | ID: mdl-34097761

Asunto(s)

Algoritmos; Pancreatocolangiografía por Resonancia Magnética; Conducto Colédoco; Redes Neurales de la Computación; Conducto Colédoco/diagnóstico por imagen; Humanos; Reproducibilidad de los Resultados

Palabras clave

Artificial; Bile duct; Magnetic resonance cholangiopancreatography (MRCP); Neural network; Stone

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Redes Neurales de la Computación / Conducto Colédoco / Pancreatocolangiografía por Resonancia Magnética Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Gastroenterol Hepatol Asunto de la revista: GASTROENTEROLOGIA Año: 2021 Tipo del documento: Article Pais de publicación: Australia

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