Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance

In this work, we assessed the ability of computerized features of nuclear morphology from diagnostic biopsy images to predict prostate cancer (CaP) progression in active surveillance (AS) patients. Improved risk characterization of AS patients could reduce over-testing of low-risk patients while dir...

Full description

Bibliographic Details
Main Authors: Sacheth Chandramouli, Patrick Leo, George Lee, Robin Elliott, Christine Davis, Guangjing Zhu, Pingfu Fu, Jonathan I. Epstein, Robert Veltri, Anant Madabhushi
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Cancers
Subjects:
prostate cancer
active surveillance
machine learning
pathology
Online Access:https://www.mdpi.com/2072-6694/12/9/2708

Internet

https://www.mdpi.com/2072-6694/12/9/2708

Similar Items