A Systematic Review of Artificial Intelligence in Prostate Cancer. Review uri icon

Overview

abstract

  • The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making. Tools like PSA levels, MRI guided biopsies, genomic biomarkers, and Gleason grading are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Nevertheless, diagnosis tracking and subsequent risk stratification often lend itself to significant subjectivity. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.

publication date

  • January 22, 2021

Identity

PubMed Central ID

  • PMC7837533

Scopus Document Identifier

  • 85076331154

Digital Object Identifier (DOI)

  • 10.2217/fon-2019-0639

PubMed ID

  • 33520879

Additional Document Info

volume

  • 13