Detecting Prostate Cancer Using Pattern Recognition Neural Networks With Flow Cytometry-Based Immunophenotyping in At-Risk Men.

This study suggests that analyzing flow cytometry immunophenotyping data with PRNNs may prove to be a useful tool to improve PCa detection and reduce the number of unnecessary prostate biopsies performed each year.
PMID: 32341637 [PubMed]

Source: Biomarker Insights - April 29, 2020 Category: General Medicine Authors: Dominguez GA, Polo AT, Roop J, Campisi AJ, Somer RA, Perzin AD, Gabrilovich DI, Kumar A Tags: Biomark Insights Source Type: research