Diagnostics Rules Generator. Phase 1. Final Report.

Abstract

This report investigates the feasibility of the automated learning of physician's diagnostic criteria for medical telemetry data from a set of examples. Using thallium myocardial scintigraphy as an illustrative domain, an architecture is established for a Diagnostic Rules Generator, and the required machine learning capability is prototyped and evaluated.

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Document Details

Document Type
Technical Report
Publication Date
Mar 03, 1988
Accession Number
ADA289450

Entities

People

  • P. R. Saunders

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Cardiac Arrhythmias
  • Cardiac Imaging Techniques
  • Cardiology
  • Cardiovascular Diseases
  • Classification
  • Computers
  • Detectors
  • Electrocardiography
  • Expert Systems
  • Feature Extraction
  • Health Services
  • Machine Learning
  • Medical Personnel
  • Neural Networks
  • Pattern Recognition

Readers

  • Electrical Engineering
  • Neural Network Machine Learning.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML