Predicting the Need to Perform Life-Saving Interventions in Trauma Patients by Using New Vital Signs and Artificial Neural Networks

Abstract

The objective is to evaluate whether descriptive data derived from EKG analysis and submitted to off-the-shelf ANN software could be used for identification of individuals who received life-saving interventions in a mixed cohort of prehospital and emergency trauma patients.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA632202

Entities

People

  • Andriy I Batchinsky
  • Corina Necsoiu
  • John A. Jones
  • Josè Salinas
  • Leopoldo C. Cancio

Organizations

  • United States Army Institute of Surgical Research

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Blood Transfusions
  • Cardiovascular Physiological Phenomena
  • Computer Science
  • Data Science
  • Emergencies
  • Frequency
  • Frequency Domain
  • Health Services
  • Heart Rate
  • Intervention
  • Neural Networks
  • Numbers
  • Signal Processing
  • Statistical Analysis
  • Vital Signs

Fields of Study

  • Medicine

Readers

  • Academic Conference Management
  • Computational Modeling and Simulation
  • Trauma or Military Medicine

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks