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Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [(68)Ga]Ga-PSMA-11 PET/MRI
PURPOSE: Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomogra...
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| Publicado no: | Eur J Nucl Med Mol Imaging |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer Berlin Heidelberg
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8113201/ https://ncbi.nlm.nih.gov/pubmed/33341915 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00259-020-05140-y |
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