897 resultados para Decision tree method
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Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.
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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).
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Objective. The objective of this study was to conduct a cost-effectiveness analysis of a universal rotavirus vaccination program among children : 5 years of age in Brazil. Methods. Considering a hypothetical annual cohort of approximately 3 300 000 newborns followed over 5 years, a decision-tree model was constructed to examine the possible clinical and economic effects of rotavirus infection with and without routine vaccination of children. Probabilities and unit costs were derived from published research and national administrative data. The impact of different estimates for key parameters was studied using sensitivity analysis. The analysis was conducted from both healthcare system and societal perspectives. Results. The vaccination program was estimated to prevent approximately 1735 351 (54%) of the 3 210 361 cases of rotavirus gastroenteritis and 703 (75%) of 933 rotavirus-associated deaths during the 5-year period. At a vaccine price of 18.6 Brazilian reais (R$) per dose, this program would cost R$121 673 966 and would save R$38 536 514 in direct costs to the public healthcare system and R$71 778 377 in direct and indirect costs to society. The program was estimated to cost R$1 028 and R$1 713 per life-years saved (LYS)from the societal and healthcare system perspectives, respectively. Conclusions. Universal rotavirus vaccination was a cost-effective strategy for both perspectives. However, these findings are highly sensitive to diarrhea incidence rate, proportion of severe cases, vaccine coverage, and vaccine price.
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Mestrado em Segurança e Higiene do Trabalho.
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OBJECTIVE: To estimate the direct costs of schizophrenia for the public sector. METHODS: A study was carried out in the state of São Paulo, Brazil, during 1998. Data from the medical literature and governmental research bodies were gathered for estimating the total number of schizophrenia patients covered by the Brazilian Unified Health System. A decision tree was built based on an estimated distribution of patients under different types of psychiatric care. Medical charts from public hospitals and outpatient services were used to estimate the resources used over a one-year period. Direct costs were calculated by attributing monetary values for each resource used. RESULTS: Of all patients, 81.5% were covered by the public sector and distributed as follows: 6.0% in psychiatric hospital admissions, 23.0% in outpatient care, and 71.0% without regular treatment. The total direct cost of schizophrenia was US$191,781,327 (2.2% of the total health care expenditure in the state). Of this total, 11.0% was spent on outpatient care and 79.2% went for inpatient care. CONCLUSIONS: Most schizophrenia patients in the state of São Paulo receive no regular treatment. The study findings point out to the importance of investing in research aimed at improving the resource allocation for the treatment of mental disorders in Brazil.
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Pós-graduação em Zootecnia - FCAV
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Hidráulica
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OBJECTIVE To analyze the incremental cost-utility ratio for the surgical treatment of hip fracture in older patients.METHODS This was a retrospective cohort study of a systematic sample of patients who underwent surgery for hip fracture at a central hospital of a macro-region in the state of Minas Gerais, Southeastern Brazil between January 1, 2009 and December 31, 2011. A decision tree creation was analyzed considering the direct medical costs. The study followed the healthcare provider’s perspective and had a one-year time horizon. Effectiveness was measured by the time elapsed between trauma and surgery after dividing the patients into early and late surgery groups. The utility was obtained in a cross-sectional and indirect manner using the EuroQOL 5 Dimensions generic questionnaire transformed into cardinal numbers using the national regulations established by the Center for the Development and Regional Planning of the State of Minas Gerais. The sample included 110 patients, 27 of whom were allocated in the early surgery group and 83 in the late surgery group. The groups were stratified by age, gender, type of fracture, type of surgery, and anesthetic risk.RESULTS The direct medical cost presented a statistically significant increase among patients in the late surgery group (p < 0.005), mainly because of ward costs (p < 0.001). In-hospital mortality was higher in the late surgery group (7.4% versus 16.9%). The decision tree demonstrated the dominance of the early surgery strategy over the late surgery strategy: R$9,854.34 (USD4,387.17) versus R$26,754.56 (USD11,911.03) per quality-adjusted life year. The sensitivity test with extreme values proved the robustness of the results.CONCLUSIONS After controlling for confounding variables, the strategy of early surgery for hip fracture in the older adults was proven to be dominant, because it presented a lower cost and better results than late surgery.
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INTRODUCTION AND OBJECTIVES: To estimate the cost-effectiveness and cost-utility of ticagrelor in the treatment of patients with acute coronary syndromes (unstable angina or myocardial infarction with or without ST-segment elevation), including patients treated medically and those undergoing percutaneous coronary intervention or coronary artery bypass grafting. METHODS: A short-term decision tree and a long-term Markov model were used to simulate the evolution of patients' life-cycles. Clinical effectiveness data were collected from the PLATO trial and resource use data were obtained from the Hospital de Santa Marta database, disease-related group legislation and the literature. RESULTS: Ticagrelor provides increases of 0.1276 life years and 0.1106 quality-adjusted life years (QALYs) per patient. From a societal perspective these clinical gains entail an increase in expenditure of €610. Thus the incremental cost per life year saved is €4780 and the incremental cost per QALY is €5517. CONCLUSIONS: The simulation results show that ticagrelor reduces events compared to clopidogrel. The costs of ticagrelor are partially offset by lower costs arising from events prevented. The use of ticagrelor in clinical practice is therefore cost-effective compared to generic clopidogrel.
American Society of Anesthesiologists Score: Still Useful After 60 Years? Results of the EuSOS Study
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OBJECTIVE: The European Surgical Outcomes Study described mortality following in-patient surgery. Several factors were identified that were able to predict poor outcomes in a multivariate analysis. These included age, procedure urgency, severity and type and the American Association of Anaesthesia score. This study describes in greater detail the relationship between the American Association of Anaesthesia score and postoperative mortality. METHODS: Patients in this 7-day cohort study were enrolled in April 2011. Consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery with a recorded American Association of Anaesthesia score in 498 hospitals across 28 European nations were included and followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Decision tree analysis with the CHAID (SPSS) system was used to delineate nodes associated with mortality. RESULTS: The study enrolled 46,539 patients. Due to missing values, 873 patients were excluded, resulting in the analysis of 45,666 patients. Increasing American Association of Anaesthesia scores were associated with increased admission rates to intensive care and higher mortality rates. Despite a progressive relationship with mortality, discrimination was poor, with an area under the ROC curve of 0.658 (95% CI 0.642 - 0.6775). Using regression trees (CHAID), we identified four discrete American Association of Anaesthesia nodes associated with mortality, with American Association of Anaesthesia 1 and American Association of Anaesthesia 2 compressed into the same node. CONCLUSION: The American Association of Anaesthesia score can be used to determine higher risk groups of surgical patients, but clinicians cannot use the score to discriminate between grades 1 and 2. Overall, the discriminatory power of the model was less than acceptable for widespread use.
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Mycobacterium avium Complex (MAC) comprises microorganisms that affect a wide range of animals including humans. The most relevant are Mycobacterium avium subspecies hominissuis (Mah) with a high impact on public health affecting mainly immunocompromised individuals and Mycobacterium avium subspecies paratuberculosis (Map) causing paratuberculosis in animals with a high economic impact worldwide. In this work, we characterized 28 human and 67 porcine Mah isolates and evaluated the relationship among them by Multiple-Locus Variable number tandem repeat Analysis (MLVA). We concluded that Mah population presented a high genetic diversity and no correlations were inferred based on geographical origin, host or biological sample. For the first time in Portugal Map strains, from asymptomatic bovine faecal samples were isolated highlighting the need of more reliable and rapid diagnostic methods for Map direct detection. Therefore, we developed an IS900 nested real time PCR with high sensitivity and specificity associated with optimized DNA extraction methodologies for faecal and milk samples. We detected 83% of 155 faecal samples from goats, cattle and sheep, and 26% of 98 milk samples from cattle, positive for Map IS900 nested real time PCR. A novel SNPs (single nucleotide polymorphisms) assay to Map characterization based on a Whole Genome Sequencing analysis was developed to elucidate the genetic relationship between strains. Based on sequential detection of 14 SNPs and on a decision tree we were able to differentiate 14 phylogenetic groups with a higher discriminatory power compared to other typing methods. A pigmented Map strain was isolated and characterized evidencing for the first time to our knowledge the existence of pigmented Type C strains. With this work, we intended to improve the ante mortem direct molecular detection of Map, to conscientiously aware for the existence of Map animal infections widespread in Portugal and to contribute to the improvement of Map and Mah epidemiological studies.
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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.
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The RMR system is still very much applied in rock mechanics engineering context. It is based on the evaluation of six weights to obtain a final rating. To obtain the final rating a considerable amount of information is needed concerning the rock mass which can be difficult to obtain in some projects or project stages at least with accuracy. In 2007 an alternative classification scheme based on the RMR, the Hierarchical Rock Mass Rating (HRMR) was presented. The main feature of this system was the adaptation to the level of knowledge existent about the rock mass to obtain the classification of the rock mass since it followed a decision tree approach. However, the HRMR was only valid for hard rock granites with low fracturing degrees. In this work, the database was enlarged with approximately 40% more cases considering other types of granite rock masses including weathered granites and based on this increased database the system was updated. Granite formations existent in the north of Portugal including Porto city are predominantly granites. Some years ago a light rail infrastructure was built in the city of Porto and surrounding municipalities whi h involved considerable challenges due to the high heterogeneity levels of the granite formations and the difficulties involved in their geomechanical characterization. In this work it is intended to provide also a contribution to improve the characterization of these formations with special emphasis to the weathered horizons. A specific subsystem applicable to the weathered formations was developed. The results of the validation of these systems are presented and show acceptable performances in identifying the correct class using less information than with the RMR system.
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Abstract This study aimed to investigate the role of ascorbate peroxidase (APX), guaiacol peroxidase (GPX), polysaccharides, and protein contents associated with the early events of postharvest physiological deterioration (PPD) in cassava roots. Increases in APX and GPX activity, as well as total protein contents occurred from 3 to 5 days of storage and were correlated with the delay of PPD. Cassava samples stained with periodic acid-Schiff (PAS) highlighted the presence of starch and cellulose. Degradation of starch granules during PPD was also detected. Slight metachromatic reaction with toluidine blue is indicative of increasing of acidic polysaccharides and may play an important role in PPD delay. Principal component analysis (PCA) classified samples according to their levels of enzymatic activity based on the decision tree model which showed GPX and total protein amounts to be correlated with PPD. The Oriental (ORI) cultivar was more susceptible to PPD.