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Artificial Neural Network to Assist Psychiatric Diagnosis

Published online by Cambridge University Press:  02 January 2018

Yizhuang Zou*
Affiliation:
Beijing Medical University, Institute of Mental Health, 100083
Yucun Shen
Affiliation:
Beijing Medical University, Institute of Mental Health, 100083
Liang Shu
Affiliation:
Beijing Medical University, Institute of Mental Health, 100083
Yufeng Wang
Affiliation:
Beijing Medical University, Institute of Mental Health, 100083
Feng Feng
Affiliation:
Beijing Huilongguan Hospital, 100085
Keqin Xu
Affiliation:
Beijing Huilongguan Hospital, 100085
Ying Qu
Affiliation:
Beijing Huilongguan Hospital, 100085
Yanming Song
Affiliation:
Beijing Huilongguan Hospital, 100085
Yixin Zhong
Affiliation:
Beijing Posts and Telecommunication University, China, 100088
Minghui Wang
Affiliation:
Beijing Posts and Telecommunication University, China, 100088
Weiquan Liu
Affiliation:
Beijing Posts and Telecommunication University, China, 100088
*
Yizhuang Zou, Washington Institute, University of Washington, 9601 Steilacoom Blvd SW, Tacoma, WA 98498-7213, USA. Fax: (206) 756-3987; e-Mail: [email protected]

Abstract

Background

Artificial Neural Network (ANN), as a potential powerful classifier, was explored to assist psychiatric diagnosis of the Composite International Diagnostic Interview (CIDI).

Method

Both Back-Propagation (BP) and Kohonen networks were developed to fit psychiatric diagnosis and programmed (using 60 cases) to classify neurosis, schizophrenia and normal people. The programmed networks were cross-tested using another 222 cases. All subjects were randomly selected from two mental hospitals in Beijing.

Results

Compared to ICD-10 diagnosis by psychiatrists, the overall kappa of BP network was 0.94 and that of Kohonen was 0.88 (both P < 0.01). In classifying patients who were difficult to diagnose, the kappa of BP was 0.69 (P < 0.01). ANN-assisted CIDI was compared with expert system assisted CIDI (kappa=0.72–0.76); ANN was more powerful than a traditional expert system.

Conclusion

ANN might be used to improve psychiatric diagnosis.

Type
Papers
Copyright
Copyright © 1996 The Royal College of Psychiatrists 

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References

Janca, A., Robins, L. N., Bucholz, K. K., et al (1992a) Comparison of Composite International Diagnostic Interview and Clinical DSM–III–R criteria Checklist Diagnosis. Acta Psychiatrica Scandinavica, 85, 440443.Google Scholar
Janca, A., Robins, L. N., Cottler, L. B., et al (1992b) Clinical observation of assessment using the Composite international Diagnostic interview, CIDI Analysis of the CIDI Field Trials – wave II at the St Louis site. British Journal of Psychiatry, 160, 815888.Google Scholar
Robins, L. N., Wing, J., Wittchen, H. U., et al (1988) The Composite International Diagnostic Interview. Archives of General Psychiatry, 45, 10691077.CrossRefGoogle ScholarPubMed
Shu, L. (1993) Field Test of Chinese Version of CIDI–Core Reliability and Validity. Chinese Mental Health Journal, 7, 208211.Google Scholar
World Health Organization (1991a) CIDI – Core Version 1.0 Interviewer's Copy. Translated by Institute of Mental Health, Beijing Medical University.Google Scholar
World Health Organization (1991b) The CIDI User's Manual. Translated by Institute of Mental Health, Beijing Medical University.Google Scholar
World Health Organization (1991c) The CIDI Computer Manual. Translated by Institute of Mental Health, Beijing Medical University.Google Scholar
Zou, Y., Shen, Y., Shu, L., et al (1994) Research on Methodology of Psychiatric Diagnosis – Artificial Neural Networks and Diagnostic Scales. Dissertation of Beijing Medical University.Google Scholar
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