Literature DB >> 18238346

Classification of somatosensory-evoked potentials recorded from patients with severe head injuries.

R M Holdaway1, M W White, A Marmarou.   

Abstract

The problem of sensory evoked potential (EP) assessment in the critical care setting to isolate damage in specific neuronal pathways, as manifested by certain abnormalities in the response waveform is being addressed using neural networks. An existing visually based grading scheme (GGS, for Greenberg grading system) for somatosensory EPs collected from patients with severe head injuries is being automated. The collection of data used in this research, which consist of somatosensory-evoked potential (SEP) waveforms collected from patients with head injuries is described. The way the system (called Pathfinder) works is described, and results obtained with it are presented.

Entities:  

Year:  1990        PMID: 18238346     DOI: 10.1109/51.59212

Source DB:  PubMed          Journal:  IEEE Eng Med Biol Mag        ISSN: 0739-5175


  2 in total

1.  Noninvasive diagnosis of coronary artery disease using a neural network algorithm.

Authors:  M Akay
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

2.  Artificial neural networks in computer-assisted classification of heart sounds in patients with porcine bioprosthetic valves.

Authors:  Z Guo; L G Durand; H C Lee; L Allard; M C Grenier; P D Stein
Journal:  Med Biol Eng Comput       Date:  1994-05       Impact factor: 2.602

  2 in total

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