Prostate cancer: early detection and assessing clinical risk using deep machine learning of high dimensional peripheral blood flow cytometric phenotyping data

Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of this study is to determine whether the T and B ce...

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Bibliographic Details

Main Authors:	Georgina Cosma, Stéphanie E McArdle, Gemma A Foulds, Simon P Hood, Stephen Reeder, Catherine Johnson, Masood A Khan, A Graham Pockley
Format:	Default Article
Published:	2021
Subjects:	Immunology not elsewhere classified prostate cancer predictive modeling immunophenotyping data flow cytometry PSA level computational analysis machine learning Immunology
Online Access:	https://hdl.handle.net/2134/17744660.v1
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