Risk Stratification Strategies for Colorectal Cancer Screening: From Logistic Regression to Artificial Intelligence

Gastrointest Endosc Clin N Am. 2020 Jul;30(3):423-440. doi: 10.1016/j.giec.2020.02.004. Epub 2020 Apr 16.

Abstract

Risk stratification is a system by which clinically meaningful separation of risk is achieved in a group of otherwise similar persons. Although parametric logistic regression dominates risk prediction, use of nonparametric and semiparametric methods, including artificial neural networks, is increasing. These statistical-learning and machine-learning methods, along with simple rules, are collectively referred to as "artificial intelligence" (AI). AI requires knowledge of study validity, understanding of model metrics, and determination of whether and to what extent the model can and should be applied to the patient or population under consideration. Further investigation is needed, especially in model validation and impact assessment.

Keywords: Cancer prevention; Colorectal cancer screening; Machine learning methods; Multivariate methods; Risk prediction models; Risk stratification.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence
  • Colorectal Neoplasms / diagnosis*
  • Early Detection of Cancer / methods*
  • Humans
  • Logistic Models
  • Risk Assessment / methods*
  • Risk Factors