• DocumentCode
    2065773
  • Title

    An expert system to aid diagnosis of epilepsy

  • Author

    Dingle, Alison A. ; Jones, Richard D. ; Carroll, Grant J.

  • Author_Institution
    Christchurch Hospital, New Zealand
  • fYear
    1993
  • fDate
    24-26 Nov 1993
  • Firstpage
    237
  • Lastpage
    239
  • Abstract
    An expert system has been developed to detect epileptiform activity in EEGs. Epileptiform events are reported as definite or probable, which helps overcome the problem of maintaining satisfactory detection rates, while minimizing false detections. The system has been evaluated on EEGs from 21 patients, a total of 380 minutes of recordings. On average the system detected 53% of epileptiform events as definite with no false detections, and 64% of events as definite or probable but at the expense of 3.5 false detections per hour. The latter detection rate compares very favourably with that of other systems. However, the outstanding feature of the system is its ability to detect 53% of events as definite with no false detections
  • Keywords
    electroencephalography; expert systems; medical diagnostic computing; performance evaluation; EEG evaluation; detection rate; epilepsy diagnosis; epileptiform activity detection; medical expert system; Biomedical engineering; Diagnostic expert systems; Electroencephalography; Epilepsy; Event detection; Expert systems; Hospitals; Medical diagnostic imaging; Medical expert systems; Physics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Neural Networks and Expert Systems, 1993. Proceedings., First New Zealand International Two-Stream Conference on
  • Conference_Location
    Dunedin
  • Print_ISBN
    0-8186-4260-2
  • Type

    conf

  • DOI
    10.1109/ANNES.1993.323034
  • Filename
    323034