Decision support system for the diagnosis of schizophrenia disorders
Braz. j. med. biol. res
;
39(1): 119-128, Jan. 2006. tab
Article
in English
| LILACS
| ID: lil-419149
RESUMO
Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Schizophrenia
/
Expert Systems
/
Diagnosis, Computer-Assisted
/
Decision Support Systems, Clinical
Type of study:
Diagnostic study
/
Prognostic study
/
Screening study
Limits:
Humans
Language:
English
Journal:
Braz. j. med. biol. res
Journal subject:
Biology
/
Medicine
Year:
2006
Type:
Article
/
Project document
Affiliation country:
Brazil
Institution/Affiliation country:
Universidade Federal de São Paulo/BR
Similar
MEDLINE
...
LILACS
LIS