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Prediction of Pathological Upgrading at Radical Prostatectomy in Prostate Cancer Eligible for Active Surveillance: A Texture Features and Machine Learning-Based Analysis of Apparent Diffusion Coefficient Maps
OBJECTIVE: To evaluate a combination of texture features and machine learning-based analysis of apparent diffusion coefficient (ADC) maps for the prediction of Grade Group (GG) upgrading in Gleason score (GS) ≤6 prostate cancer (PCa) (GG1) and GS 3 + 4 PCa (GG2). MATERIALS AND METHODS: Fifty-nine pa...
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| Publicado no: | Front Oncol |
|---|---|
| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7890009/ https://ncbi.nlm.nih.gov/pubmed/33614487 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2020.604266 |
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