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Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer
Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic dat...
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| Wydane w: | Front Genet |
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| Główni autorzy: | , , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Frontiers Media S.A.
2020
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7723980/ https://ncbi.nlm.nih.gov/pubmed/33324443 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2020.550894 |
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