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Predicting Microenvironment in CXCR4- and FAP-Positive Solid Tumors-A Pan-Cancer Machine Learning Workflow for Theranostic Target Structures.
Marquardt, André; Hartrampf, Philipp; Kollmannsberger, Philip; Solimando, Antonio G; Meierjohann, Svenja; Kübler, Hubert; Bargou, Ralf; Schilling, Bastian; Serfling, Sebastian E; Buck, Andreas; Werner, Rudolf A; Lapa, Constantin; Krebs, Markus.
Afiliación
  • Marquardt A; Department of Pathology, Klinikum Stuttgart, 70174 Stuttgart, Germany.
  • Hartrampf P; Department of Nuclear Medicine, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Kollmannsberger P; Center for Computational and Theoretical Biology, University of Würzburg, 97074 Würzburg, Germany.
  • Solimando AG; Guido Baccelli Unit of Internal Medicine, Department of Precision and Regenerative Medicine and Ionian Area-(DiMePRe-J), School of Medicine, Aldo Moro University of Bari, 70124 Bari, Italy.
  • Meierjohann S; IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, 70124 Bari, Italy.
  • Kübler H; Institute of Pathology, University of Würzburg, 97080 Würzburg, Germany.
  • Bargou R; Department of Urology and Pediatric Urology, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Schilling B; Comprehensive Cancer Center Mainfranken, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Serfling SE; Department of Dermatology, University Hospital of Würzburg, 97080 Würzburg, Germany.
  • Buck A; Department of Nuclear Medicine, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Werner RA; Department of Nuclear Medicine, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Lapa C; Department of Nuclear Medicine, University Hospital Würzburg, 97080 Würzburg, Germany.
  • Krebs M; The Russell H Morgan Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Cancers (Basel) ; 15(2)2023 Jan 06.
Article en En | MEDLINE | ID: mdl-36672341
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza