6 resultados para discriminate
em Repositório da Produção Científica e Intelectual da Unicamp
Resumo:
The purpose of this study was to evaluate the effectiveness of mature red cell and reticulocyte parameters under three conditions: iron deficiency anemia, anemia of chronic disease, and anemia of chronic disease associated with absolute iron deficiency. Peripheral blood cells from 117 adult patients with anemia were classified according to iron status, and inflammatory activity, and the results of a hemoglobinopathy investigation as: iron deficiency anemia (n=42), anemia of chronic disease (n=28), anemia of chronic disease associated with iron deficiency anemia (n=22), and heterozygous β thalassemia (n=25). The percentage of microcytic red cells, hypochromic red cells, and levels of hemoglobin content in both reticulocytes and mature red cells were determined. Receiver operating characteristic analysis was used to evaluate the accuracy of the parameters in differentiating between the different types of anemia. There was no significant difference between the iron deficient group and anemia of chronic disease associated with absolute iron deficiency in respect to any parameter. The percentage of hypochromic red cells was the best parameter to discriminate anemia of chronic disease with and without absolute iron deficiency (area under curve=0.785; 95% confidence interval: 0.661-0.909, with sensitivity of 72.7%, and specificity of 70.4%; cut-off value 1.8%). The formula microcytic red cells minus hypochromic red cells was very accurate in differentiating iron deficiency anemia and heterozygous β thalassemia (area under curve=0.977; 95% confidence interval: 0.950-1.005; with sensitivity of 96.2%, and specificity of 92.7%; cut-off value 13.8). The indices related to red cells and reticulocytes have a moderate performance in identifying absolute iron deficiency in patients with anemia of chronic disease.
Resumo:
Introductions: In the care of hypertension, it is important that health professionals possess available tools that allow evaluating the impairment of the health-related quality of life, according to the severity of hypertension and the risk for cardiovascular events. Among the instruments developed for the assessment of health-related quality of life, there is the Mini-Cuestionario of Calidad de Vida en la Hipertensión Arterial (MINICHAL) recently adapted to the Brazilian culture. Objective: To estimate the validity of known groups of the Brazilian version of the MINICHAL regarding the classification of risk for cardiovascular events, symptoms, severity of dyspnea and target-organ damage. Methods: Data of 200 hypertensive outpatients concerning sociodemographic and clinical information and health-related quality of life were gathered by consulting the medical charts and the application of the Brazilian version of MINICHAL. The Mann-Whitney test was used to compare health-related quality of life in relation to symptoms and target-organ damage. The Kruskal-Wallis test and ANOVA with ranks transformation were used to compare health-related quality of life in relation to the classification of risk for cardiovascular events and intensity of dyspnea, respectively. Results: The MINICHAL was able to discriminate health-related quality of life in relation to symptoms and kidney damage, but did not discriminate health-related quality of life in relation to the classification of risk for cardiovascular events. Conclusion: The Brazilian version of the MINICHAL is a questionnaire capable of discriminating differences on the health‑related quality of life regarding dyspnea, chest pain, palpitation, lipothymy, cephalea and renal damage.Fundamento: No cuidado ao hipertenso, é importante que o profissional de saúde disponha de ferramentas que possibilitem avaliar o comprometimento da qualidade de vida relacionada à saúde, de acordo com a gravidade da hipertensão e o risco para eventos cardiovasculares. Dentre os instrumentos criados para avaliação da qualidade de vida relacionada à saúde, destaca-se o Mini-Cuestionario de Calidad de Vida en la Hipertensión Arterial (MINICHAL), recentemente adaptado para a cultura brasileira. Objetivo: Estimar a validade de grupos conhecidos da versão brasileira do MINICHAL em relação à classificação de risco para eventos cardiovasculares, sintomas, intensidade da dispneia e lesões de órgãos-alvo. Métodos: Foram investigados 200 hipertensos em seguimento ambulatorial, cujos dados sociodemográficos, clínicos e de qualidade de vida relacionada à saúde foram obtidos por meio de consulta ao prontuário e da aplicação da versão brasileira do MINICHAL. O teste de Mann-Whitney foi utilizado para comparar qualidade de vida relacionada à saúde em relação aos sintomas e às lesões de órgãos-alvo. Teste de Kruskal-Wallis e ANOVA com transformação nos ranks foram empregados para comparar qualidade de vida relacionada à saúde em relação à classificação de risco para eventos cardiovasculares e intensidade da dispneia, respectivamente. Resultados: O MINICHAL discriminou qualidade de vida relacionada à saúde em relação aos sintomas e dano renal (lesões de órgãos-alvo), porém não discriminou qualidade de vida relacionada à saúde em relação à classificação de risco para eventos cardiovasculares. Conclusão: A versão brasileira do MINICHAL é um instrumento capaz de discriminar diferenças na qualidade de vida relacionada à saúde em relação aos sintomas de dispneia, precordialgia, palpitação, lipotímia, cefaleia e presença de dano renal.
Resumo:
Remotely sensed imagery has been widely used for land use/cover classification thanks to the periodic data acquisition and the widespread use of digital image processing systems offering a wide range of classification algorithms. The aim of this work was to evaluate some of the most commonly used supervised and unsupervised classification algorithms under different landscape patterns found in Rondônia, including (1) areas of mid-size farms, (2) fish-bone settlements and (3) a gradient of forest and Cerrado (Brazilian savannah). Comparison with a reference map based on the kappa statistics resulted in good to superior indicators (best results - K-means: k=0.68; k=0.77; k=0.64 and MaxVer: k=0.71; k=0.89; k=0.70 respectively for three areas mentioned). Results show that choosing a specific algorithm requires to take into account both its capacity to discriminate among various spectral signatures under different landscape patterns as well as a cost/benefit analysis considering the different steps performed by the operator performing a land cover/use map. it is suggested that a more systematic assessment of several options of implementation of a specific project is needed prior to beginning a land use/cover mapping job.
Resumo:
PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
Resumo:
Universidade Estadual de Campinas . Faculdade de Educação Física
Resumo:
Universidade Estadual de Campinas . Faculdade de Educação Física