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Detecting Prostate Cancer Using Pattern Recognition Neural Networks With Flow Cytometry-Based Immunophenotyping in At-Risk Men
Current screening methods for prostate cancer (PCa) result in a large number of false positives making it difficult for clinicians to assess disease status, thus warranting advancements in screening and early detection methods. The goal of this study was to design a liquid biopsy test that uses flow...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
SAGE Publications
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169353/ https://www.ncbi.nlm.nih.gov/pubmed/32341637 http://dx.doi.org/10.1177/1177271920913320 |