• DocumentCode
    2394456
  • Title

    A neural net screening of psychiatric patients

  • Author

    Yana, Kazuo ; Kawachi, Kohji ; Iida, Kazuhiro ; Okubo, Yoshio ; Tohru, Michio ; Okuyama, Fumio

  • Author_Institution
    Dept. of Electron. Inf., Hosei Univ., Tokyo, Japan
  • fYear
    1994
  • fDate
    1994
  • Firstpage
    1366
  • Abstract
    Describes a method for screening psychiatric patients based on a questionnaire consisting of simple yes/no questions relating to physical, mental conditions and subjective symptoms which is provided at their first visit to the hospital. The analysis of the questionnaire is important to understand patients´ background. One hundred filled out questionnaires were utilized for constructing and evaluating a neural net classifier which classifies patients into three categories i.e. schizophrenic, emotional and neurotic disorders with average correct prediction rate of 74.7%. The rate was 18.0% higher than the result given by experienced medical doctors and the method will be a useful mean for automatic screening the psychiatric patients
  • Keywords
    medical expert systems; automatic screening; average correct prediction rate; experienced medical doctors; first visit; hospital; mental conditions; neural net classifier; neural net screening; neurotic disorders; patient background; physical conditions; psychiatric patients; questionnaire; simple yes/no questions; subjective symptoms; three layer perceptron; Biomedical informatics; Dentistry; Hospitals; Laboratories; Medical diagnostic imaging; Mood; National electric code; Neural networks; Psychology; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-2050-6
  • Type

    conf

  • DOI
    10.1109/IEMBS.1994.415475
  • Filename
    415475