Navegando por Palavras-chave "Fuzzy logic"
Agora exibindo 1 - 4 de 4
Resultados por página
Opções de Ordenação
- ItemSomente MetadadadosFuzzy cognitive map in differential diagnosis of alterations in urinary elimination: A nursing approach(Elsevier B.V., 2013-03-01) Baena de Moraes Lopes, Maria Helena; Siqueira Ortega, Neli Regina; Panse Silveira, Paulo Sergio; Massad, Eduardo; Higa, Rosangela; Marin, Heimar de Fatima [UNIFESP]; Universidade Estadual de Campinas (UNICAMP); Universidade de São Paulo (USP); Universidade Federal de São Paulo (UNIFESP)Purpose: To develop a decision support system to discriminate the diagnoses of alterations in urinary elimination, according to the nursing terminology of NANDA International (NANDA-I).Methods: A fuzzy cognitive map (FCM) was structured considering six possible diagnoses: stress urinary incontinence, reflex urinary incontinence, urge urinary incontinence, functional urinary incontinence, total urinary incontinence and urinary retention; and 39 signals associated with them. the model was implemented in Microsoft Visual C++(R) Edition 2005 and applied in 195 real cases. Its performance was evaluated through the agreement test, comparing its results with the diagnoses determined by three experts (nurses). the sensitivity and specificity of the model were calculated considering the expert's opinion as a gold standard. in order to compute the Kappa's values we considered two situations, since more than one diagnosis was possible: the overestimation of the accordance in which the case was considered as concordant when at least one diagnoses was equal; and the underestimation of the accordance, in which the case was considered as discordant when at least one diagnosis was different.Results: the overestimation of the accordance showed an excellent agreement (kappa = 0.92, p < 0.0001); and the underestimation provided a moderate agreement (kappa = 0.42, p < 0.0001). in general the FCM model showed high sensitivity and specificity, of 0.95 and 0.92, respectively, but provided a low specificity value in determining the diagnosis of urge urinary incontinence (0.43) and a low sensitivity value to total urinary incontinence (0.42).Conclusions: the decision support system developed presented a good performance compared to other types of expert systems for differential diagnosis of alterations in urinary elimination. Since there are few similar studies in the literature, we are convinced of the importance of investing in this kind of modeling, both from the theoretical and from the health applied points of view.Limitations: in spite of the good results, the FCM should be improved to identify the diagnoses of urge urinary incontinence and total urinary incontinence. (C) 2012 Elsevier Ireland Ltd. All rights reserved.
- ItemSomente MetadadadosModel for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic(Lippincott Williams & Wilkins, 2009-09-01) Lopes, Maria Helena Baena de Moraes; Ortega, Neli Regina Siqueira; Massad, Eduardo [UNIFESP]|Marin, Heimar de Fatima [UNIFESP]; Universidade Estadual de Campinas (UNICAMP); Universidade de São Paulo (USP); Universidade Federal de São Paulo (UNIFESP)Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.
- ItemSomente MetadadadosNeural network and fuzzy logic statistical downscaling of atmospheric circulation-type specific weather pattern for rainfall forecasting(Elsevier B.V., 2014-09-01) Valverde, M. C.; Araujo, Ernesto [UNIFESP]; Campos Velho, H.; Universidade Federal do ABC (UFABC); Inteligencia Artificial Tecnol IATECH; Universidade Federal de São Paulo (UNIFESP); FCMMG; INPEThe weather natural disaster prevention for quantitative daily rainfall forecasting derived from the SACZ-ULCV weather pattern is proposed in this paper by using intertwined statistical downscaling (SD) and soft computing (SC) approaches. the fuzzy statistical downscaling (FSD) is first introduced and, then, employed for dealing with the SACZ-ULCV atmospheric circulation-type specific weather pattern for supporting daily precipitation (rainfall) forecasting. This paper also addresses the performance comparison of the FSD and the neural statistical downscaling (NSD) approaches when taking into account 12 major urban centers all over the state of São Paulo, Brazil, for the summer period. the SACZ-ULCV summer pattern is identified in meteorological satellite images when the cloudiness of the Brazilian Northeast upper level cyclonic vortices (ULCV) meets the South Atlantic convergence zone (SACZ). Increasing the convection and the cloudiness over the Southeast region of Brazil, the SACZ-ULCV causes severe rainfalls and thunderstorms with impact on the population. Finding a manner to anticipate these extreme rainfall events is of vital importance for minimizing or avoiding disasters, and saving lives. Daily rainfall forecasting had their performance improved either by using the proposed FSD or NSD in comparison to the Multilinear Regression ETA model. Results demonstrate the FSD and the NSD become feasible alternatives for achieving a correspondence from meteorological and thermo-dynamical variables to the daily rainfall variable. (C) 2014 Elsevier B.V. All rights reserved.
- ItemSomente MetadadadosSupport system for decision making in the identification of risk for body dysmorphic disorder: A fuzzy model(Elsevier B.V., 2013-09-01) Brito, Maria José Azevedo de [UNIFESP]; Nahas, Fabio Xerfan [UNIFESP]; Ortega, Neli Regina Siqueira; Cordás, Táki Athanássios; Dini, Gal Moreira [UNIFESP]; Sabino Neto, Miguel [UNIFESP]; Ferreira, Lydia Masako [UNIFESP]; Universidade Federal de São Paulo (UNIFESP); Universidade de São Paulo (USP)Purpose: To develop a fuzzy linguistic model to quantify the level of distress of patients seeking cosmetic surgery. Body dysmorphic disorder (BDD) is a mental condition related to body image relatively common among cosmetic surgery patients; it is difficult to diagnose and is a significant cause of morbidity and mortality. Fuzzy cognitive maps are an efficient tool based on human knowledge and experience that can handle uncertainty in identifying or grading BDD symptoms and the degree of body image dissatisfaction. Individuals who seek cosmetic procedures suffer from some degree of dissatisfaction with appearance.Methods: A fuzzy model was developed to measure distress levels in cosmetic surgery patients based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), diagnostic criterion B for BDD. We studied 288 patients of both sexes seeking abdominoplasty, rhinoplasty, or rhytidoplasty in a university hospital.Results: Patient distress ranged from none to severe (range=7.5-31.6; cutoff point=18; area under the ROC curve=0.923). There was a significant agreement between the fuzzy model and DSM-IV criterion B (kappa = 0.805; p<0.001).Conclusion: the fuzzy model measured distress levels with good accuracy, indicating that it can be used as a screening tool in cosmetic surgery and psychiatric practice. (C) 2013 Elsevier Ireland Ltd. All rights reserved.