A Predictive Model of Resectability for Patients with Bronchogenic Carcinoma

Abstract

A computerized model based on Bayes' theorem was designed to predict whether bronchogenic cancer could be researched for cure. Beginning on 1 January, 1986, 100 consecutive patients undergoing thoracotomy for suspected lung cancer were prospectively analyzed. Eighty-five patients were found to have bronchogenic cancer and the remaining 15 were excluded from the study. Thirty-three risk factors were used to characterize the patient population. Bayesian conditional probabilities were derived from literature values and physician estimates. Keywords: Bayesian theory; Cancer; Pulmonary function; Reprints; Surgery.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA212580

Entities

People

  • F. H. Edwards
  • G. M. Graeber
  • R. A. Albus

Organizations

  • Walter Reed Army Institute of Research

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Arteries
  • Cancer
  • Clinical Trials
  • Computer Programs
  • Computers
  • Diseases And Disorders
  • Health Services
  • Lung Cancer
  • Medical Personnel
  • Neoplasms
  • Predictive Modeling
  • Probability
  • Risk Factors
  • Surgery
  • Thorax

Readers

  • Computational Modeling and Simulation
  • Statistical inference.
  • Trauma or Military Medicine

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference