Weakly supervised deep learning to predict recurrence in low-grade endometrial cancer from multiplexed immunofluorescence images.

Jiménez-Sánchez, Daniel; López-Janeiro, Álvaro; Villalba-Esparza, María; Ariz, Mikel; Kadioglu, Ece; Masetto, Ivan; Goubert, Virginie; Lozano, Maria D; Melero, Ignacio; Hardisson, David; Ortiz-de-Solórzano, Carlos; de Andrea, Carlos E

Jiménez-Sánchez, Daniel; López-Janeiro, Álvaro; Villalba-Esparza, María; Ariz, Mikel; Kadioglu, Ece; Masetto, Ivan; Goubert, Virginie; Lozano, Maria D; Melero, Ignacio; Hardisson, David; Ortiz-de-Solórzano, Carlos; de Andrea, Carlos E.

Afiliação

Jiménez-Sánchez D; Program of Solid Tumors and Biomarkers, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.
López-Janeiro Á; Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain.
Villalba-Esparza M; Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain.
Ariz M; Department of Pathology, Hospital Universitario La Paz, IdiPAZ, Madrid, Spain.
Kadioglu E; Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain.
Masetto I; Navarra Institute for Health Research (IdISNA), Pamplona, Spain.
Goubert V; Program of Solid Tumors and Biomarkers, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.
Lozano MD; Navarra Institute for Health Research (IdISNA), Pamplona, Spain.
Melero I; Lunaphore Technologies SA, Tolochenaz, Switzerland.
Hardisson D; Akoya Biosciences, Marlborough, MA, USA.
Ortiz-de-Solórzano C; Akoya Biosciences, Marlborough, MA, USA.
de Andrea CE; Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain.

NPJ Digit Med ; 6(1): 48, 2023 Mar 23.

Article em En | MEDLINE | ID: mdl-36959234

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: NPJ Digit Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha País de publicação: Reino Unido

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