Improved Breast Cancer Research Through Automated Matching of Patients to Clinical Trials

Abstract

An enhanced Web based prototype intelligent agent/expert system for matching breast cancer patients to clinical trials has been built. It allows for cost preferences to be entered. Therefore, the system user can choose to rule patients out of trials as quickly as possible without regard to the cost of tests necessary to do this. They can choose have questions appear so that the patient is ruled out of the trial with the minimal set of costs (tests) or can choose some combination of approaches. The system has been tested with 12 protocols and designed for maximal responsiveness and scalability as new protocols are added. The files of 178 former patients have been used to test the accuracy of the system. Additionally, the files of 57 current patients have been tested for eligibility. Patients for each of the protocols were correctly found eligible for one or more trials. We have also developed a prototype system to quickly add new clinical trials. This has been successfully used by novices to enter new trials.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA408023

Entities

People

  • Dmitry B. Goldgof
  • Jeffrey P Krischer
  • Lawrence O. Hall

Organizations

  • University of South Florida

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Biomedical Research
  • Breast Cancer
  • Cardiac Arrhythmias
  • Clinical Trials
  • Computer Science
  • Cost Reductions
  • Expert Systems
  • Health Services
  • Heart Diseases
  • Intelligent Agents
  • Lymph Nodes
  • Medical Personnel
  • Neoplasms
  • Rule Based Systems
  • Test Sets

Fields of Study

  • Medicine

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Database Systems and Applications