Automated Identification of Abnormal Cardiotocograms Using Neural Network Visualization Techniques

Abstract

The cardiotocogram (CTG) is a display of the fetal heart rate and maternal uterine activity over time. An automated system for CTG analysis can be used as a decision support tool in a clinical setting%%. We present an automated system for the identification of abnormal patterns in the intrapartum (labor) CTG. We extract discriminating features from the CTG and then use techniques based upon the Neuroscale algorithm to project these features onto a two-dimensional visualization space. The locations of the projected features in the visualization space correlate retrospectively with an expert's assessment of the CTG's pattern.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412473

Entities

People

  • C. W. Redman
  • L. Impey
  • L. Tarassenko
  • M. Moulden
  • S. Cazares

Organizations

  • University of Oxford

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Amplitude
  • Control Systems
  • Deceleration
  • Engineering
  • Fungi
  • Health Services
  • Heart Rate
  • Military Research
  • Neural Networks
  • Physiological Monitoring
  • Pressure Transducers
  • Quadrants
  • Trajectories
  • Two Dimensional
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Surface Coatings Technology.
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • AI & ML
  • Space