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

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)423-440
Number of pages18
JournalGastrointestinal Endoscopy Clinics of North America
Volume30
Issue number3
DOIs
StatePublished - Jul 2020

Keywords

  • Cancer prevention
  • Colorectal cancer screening
  • Machine learning methods
  • Multivariate methods
  • Risk prediction models
  • Risk stratification

ASJC Scopus subject areas

  • Gastroenterology

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