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Machine Learning Integrating 99mTc Sestamibi SPECT/CT and Radiomics Data Achieves Optimal Characterization of Renal Oncocytic Tumors.
Klontzas, Michail E; Koltsakis, Emmanouil; Kalarakis, Georgios; Trpkov, Kiril; Papathomas, Thomas; Karantanas, Apostolos H; Tzortzakakis, Antonios.
Afiliação
  • Klontzas ME; Department of Medical Imaging, University Hospital of Heraklion, Heraklion 71110, Greece.
  • Koltsakis E; Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology (FORTH), Heraklion 70013, Greece.
  • Kalarakis G; Department of Radiology, School of Medicine, University of Crete, Voutes Campus, Heraklion 71110, Greece.
  • Trpkov K; Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm 17177, Sweden.
  • Papathomas T; Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm 17177, Sweden.
  • Karantanas AH; Division of Radiology, Department for Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm 14152, Sweden.
  • Tzortzakakis A; Alberta Precision Labs, Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2L 2K5, Canada.
Cancers (Basel) ; 15(14)2023 Jul 09.
Article em En | MEDLINE | ID: mdl-37509214
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article