Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools

Abstract

Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for building such tools with application to the Prostate Biopsy Collaborative Group prostate cancer risk prediction tool.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 15, 2019
Source ID
10.1186/s12874-019-0839-0

Entities

People

  • Amanda De Hoedt
  • Andrew J. Vickers
  • Cedric Poyet
  • Donna Ankerst
  • Emily Vertosick
  • Javier Hernandez
  • Johanna Tolksdorf
  • Karim Saba
  • Lourdes Guerrios
  • Michael A Liss
  • Michael W Kattan
  • Robin J Leach
  • Stephen A. Boorjian
  • Stephen J. Freedland

Organizations

  • Congressionally Directed Medical Research Programs
  • National Cancer Institute

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML