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...

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Detalles Bibliográficos
Autores principales: Dominguez, George A, Polo, Alexander T, Roop, John, Campisi, Anthony J, Somer, Robert A, Perzin, Adam D, Gabrilovich, Dmitry I, Kumar, Amit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Original Research
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169353/
https://www.ncbi.nlm.nih.gov/pubmed/32341637
http://dx.doi.org/10.1177/1177271920913320

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