| Full text | |
| Author(s): |
Denise Razzouk
[1]
;
Jair de Jesus Mari
[2]
;
Itiro Shirakawa
[3]
;
Jacques Wainer
;
Daniel Sigulem
[5]
Total Authors: 5
|
| Affiliation: | [1] Universidade Federal de São Paulo. Psychiatry Department - Brasil
[2] Universidade Federal de São Paulo. Psychiatry Department - Brasil
[3] Universidade Federal de São Paulo. Psychiatry Department - Brasil
[5] Universidade Federal de São Paulo. Department of Medical Informatics - Brasil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | Revista Brasileira de Psiquiatria; v. 28, n. 1, p. 5-9, 2006-03-00. |
| Abstract | |
OBJETIVE: Research on clinical reasoning has been useful in developing expert systems. These tools are based on Artificial Intelligence techniques which assist the physician in the diagnosis of complex diseases. The development of these systems is based on a cognitive model extracted through the identification of the clinical reasoning patterns applied by experts within the clinical decision-making context. This study describes the method of knowledge acquisition for the identification of the triggering symptoms used in the reasoning of three experts for the diagnosis of schizophrenia. METHOD: Three experts on schizophrenia, from two University centers in Sao Paulo, were interviewed and asked to identify and to represent the triggering symptoms for the diagnosis of schizophrenia according to the graph methodology. RESULTS: Graph methodology showed a remarkable disagreement on how the three experts established their diagnosis of schizophrenia. They differed in their choice of triggering-symptoms for the diagnosis of schizophrenia: disorganization, blunted affect and thought disturbances. CONCLUSIONS: The results indicate substantial differences between the experts as to their diagnostic reasoning patterns, probably under the influence of different theoretical tendencies. The disorganization symptom was considered to be the more appropriate to represent the heterogeneity of schizophrenia and also, to further develop an expert system for the diagnosis of schizophrenia. (AU) | |