How do experts recognize schizophrenia: the role of the disorganization symptom
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Psychiatry (São Paulo. 1999. Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462006000100003 |
Resumo: | 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. |
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Brazilian Journal of Psychiatry (São Paulo. 1999. Online) |
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How do experts recognize schizophrenia: the role of the disorganization symptomArtificial intelligenceExpert systemsKnowledge acquisitionSchizophreniaPsychotic disordersOBJETIVE: 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.Associação Brasileira de Psiquiatria2006-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462006000100003Brazilian Journal of Psychiatry v.28 n.1 2006reponame:Brazilian Journal of Psychiatry (São Paulo. 1999. Online)instname:Associação Brasileira de Psiquiatria (ABP)instacron:ABP10.1590/S1516-44462006000100003info:eu-repo/semantics/openAccessRazzouk,DeniseMari,Jair de JesusShirakawa,ItiroWainer,JacquesSigulem,Danieleng2006-03-24T00:00:00Zoai:scielo:S1516-44462006000100003Revistahttp://www.bjp.org.br/ahead_of_print.asphttps://old.scielo.br/oai/scielo-oai.php||rbp@abpbrasil.org.br1809-452X1516-4446opendoar:2006-03-24T00:00Brazilian Journal of Psychiatry (São Paulo. 1999. Online) - Associação Brasileira de Psiquiatria (ABP)false |
dc.title.none.fl_str_mv |
How do experts recognize schizophrenia: the role of the disorganization symptom |
title |
How do experts recognize schizophrenia: the role of the disorganization symptom |
spellingShingle |
How do experts recognize schizophrenia: the role of the disorganization symptom Razzouk,Denise Artificial intelligence Expert systems Knowledge acquisition Schizophrenia Psychotic disorders |
title_short |
How do experts recognize schizophrenia: the role of the disorganization symptom |
title_full |
How do experts recognize schizophrenia: the role of the disorganization symptom |
title_fullStr |
How do experts recognize schizophrenia: the role of the disorganization symptom |
title_full_unstemmed |
How do experts recognize schizophrenia: the role of the disorganization symptom |
title_sort |
How do experts recognize schizophrenia: the role of the disorganization symptom |
author |
Razzouk,Denise |
author_facet |
Razzouk,Denise Mari,Jair de Jesus Shirakawa,Itiro Wainer,Jacques Sigulem,Daniel |
author_role |
author |
author2 |
Mari,Jair de Jesus Shirakawa,Itiro Wainer,Jacques Sigulem,Daniel |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Razzouk,Denise Mari,Jair de Jesus Shirakawa,Itiro Wainer,Jacques Sigulem,Daniel |
dc.subject.por.fl_str_mv |
Artificial intelligence Expert systems Knowledge acquisition Schizophrenia Psychotic disorders |
topic |
Artificial intelligence Expert systems Knowledge acquisition Schizophrenia Psychotic disorders |
description |
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. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462006000100003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462006000100003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1516-44462006000100003 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Psiquiatria |
publisher.none.fl_str_mv |
Associação Brasileira de Psiquiatria |
dc.source.none.fl_str_mv |
Brazilian Journal of Psychiatry v.28 n.1 2006 reponame:Brazilian Journal of Psychiatry (São Paulo. 1999. Online) instname:Associação Brasileira de Psiquiatria (ABP) instacron:ABP |
instname_str |
Associação Brasileira de Psiquiatria (ABP) |
instacron_str |
ABP |
institution |
ABP |
reponame_str |
Brazilian Journal of Psychiatry (São Paulo. 1999. Online) |
collection |
Brazilian Journal of Psychiatry (São Paulo. 1999. Online) |
repository.name.fl_str_mv |
Brazilian Journal of Psychiatry (São Paulo. 1999. Online) - Associação Brasileira de Psiquiatria (ABP) |
repository.mail.fl_str_mv |
||rbp@abpbrasil.org.br |
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1754212553246900224 |