Radiological Image Traits Predictive of Cancer Status in Pulmonary Nodules

Abstract

Purpose: We propose a systematic methodology to quantify incidentally identified pulmonary nodules based on observed radiological traits (semantics) quantified on a point scale and a machine-learning method using these data to predict cancer status.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 14, 2017
Source ID
10.1158/1078-0432.ccr-15-3102

Entities

People

  • Gary T. Smith
  • Li Qian
  • Matthew B. Schabath
  • Pierre P. Massion
  • Robert J Gillies
  • Ronald C. Walker
  • Sanja Antic
  • Thomas Atwater
  • Ying Liu
  • Yoganand Balagurunathan

Organizations

  • Florida Department of Health
  • H. Lee Moffitt Cancer Center & Research Institute
  • National Institutes of Health
  • Tianjin Medical University
  • United States Department of Defense
  • Vanderbilt University

Tags

Fields of Study

  • Medicine
  • Physics

Readers

  • Aviation Safety Risk Assessment.
  • Infectious Disease/Epidemiology
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference