Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry Academic Article uri icon

Overview

MeSH Major

  • Antidepressive Agents
  • Depressive Disorder
  • Psychotherapy

abstract

  • A risk score created by a ML based algorithm, that utilizes standard 16 coronary segment stenosis and composition information derived from detailed CCTA reading, has greater prognostic accuracy than current CCTA integrated risk scores. These findings indicate that a ML based algorithm can improve the integration of CCTA derived plaque information to improve risk stratification.

authors

publication date

  • January 2018

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1016/j.jcct.2018.04.011

PubMed ID

  • 29753765

Additional Document Info