Evolving an optimal decision template for combining classifiers.

In this paper, we aim to develop an effective combining algorithm for ensemble learning systems. The Decision Template method, one of the most popular combining algorithms for ensemble systems, does not perform well when working on certain datasets like those having imbalanced data. Moreover, point estimation by computing the average value on the outputs of base classifiers in the Decision Template method is sometimes not a good representation, especially for skewed datasets. Here we propose to search for an optimal decision template in the combining algorithm for a heterogeneous ensemble. To do this, we first generate the base classifier by training the pre-selected learning algorithms on the given training set. The meta-data of the training set is then generated via cross validation. Using the Artificial Bee Colony algorithm, we search for the optimal template that minimizes the empirical 0–1 loss function on the training set. The class label is assigned to the unlabeled sample based on the maximum of the similarity between the optimal decision template and the sample’s meta-data. Experiments conducted on the UCI datasets demonstrated the superiority of the proposed method over several benchmark algorithms

Confidence in prediction: an approach for dynamic weighted ensemble.

Combining classifiers in an ensemble is beneficial in achieving better prediction than using a single classifier. Furthermore, each classifier can be associated with a weight in the aggregation to boost the performance of the ensemble system. In this work, we propose a novel dynamic weighted ensemble method. Based on the observation that each classifier provides a different level of confidence in its prediction, we propose to encode the level of confidence of a classifier by associating with each classifier a credibility threshold, computed from the entire training set by minimizing the entropy loss function with the mini-batch gradient descent method. On each test sample, we measure the confidence of each classifier’s output and then compare it to the credibility threshold to determine whether a classifier should be attended in the aggregation. If the condition is satisfied, the confidence level and credibility threshold are used to compute the weight of contribution of the classifier in the aggregation. By this way, we are not only considering the presence but also the contribution of each classifier based on the confidence in its prediction on each test sample. The experiments conducted on a number of datasets show that the proposed method is better than some benchmark algorithms including a non-weighted ensemble method, two dynamic ensemble selection methods, and two Boosting methods

Multi-Omics strategy for cell culture medium optimization in Fed-Bach CHO Cell Cultivation

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GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs

This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian Processes (GP), and to states represented as a weighted sum of Gaussians. The key attribute of GP-SUM is that it does not rely on linearizations of the dynamic or observation models, or on unimodal Gaussian approximations of the belief, hence enables tracking complex state distributions. The algorithm can be seen as a combination of a sampling-based filter with a probabilistic Bayes filter. On the one hand, GP-SUM operates by sampling the state distribution and propagating each sample through the dynamic system and observation models. On the other hand, it achieves effective sampling and accurate probabilistic propagation by relying on the GP form of the system, and the sum-of-Gaussian form of the belief. We show that GP-SUM outperforms several GP-Bayes and Particle Filters on a standard benchmark. We also demonstrate its use in a pushing task, predicting with experimental accuracy the naturally occurring non-Gaussian distributions.Comment: WAFR 2018, 16 pages, 7 figure

The Esophageal Anastomosis: How Improving Blood Supply Affects Leak Rate

Esophageal leak. Anastomosis. VEGF. Delay phenomenon surgical preparation of the conduit in order to reduce morbidity and optimize patient outcomes

Relationship Between Obesity and Diabetes in a US Adult Population: Findings from the National Health and Nutrition Examination Survey, 1999–2006

# The Author(s) 2010. This article is published with open access at Springerlink.com Background Obesity is one of the most important modifiable risk factors for the prevention of type 2 diabetes. The aim of this study was to examine the prevalence of diabetes with increasing severity of obesity and the distribution of HbA1c levels in diabetics participating in the latest National Health and Nutrition Examination Survey (NHANES). Methods Data from a representative sample of adults with diabetes participating in the NHANES between 1999 and 2006 were reviewed. The prevalence of diabetes and levels of fasting glucose, insulin, c-peptide, and HbA1c were examined across different weight classes with normal weight, overweight, and obesity classes 1, 2, and 3 were defined as body mass index (BMI) of <25.0, 25.0–29.9, 30.0–34.9, 35.0–39.9, and equal to 40.0, respectively. The distribution of HbA1c levels among adults with diabetes was also examined. Results There were 2,894 adults with diabetes (13.6%) among the 21,205 surveyed participants. Among the adults with diabetes, the mean age was 59 years, the mean fasting glucose was 155±2 mg/dl, and the mean HbA1c was 7.2%; 80.3 % of diabetics were considered overweight (BMI≥25) and 49.1 % of diabetics were considered obese (BMI≥30). Presented as a poster presentation at the American Society fo

Influenza A H5N1 and HIV co-infection: case report

<p>Abstract</p> <p>Background</p> <p>The role of adaptive immunity in severe influenza is poorly understood. The occurrence of influenza A/H5N1 in a patient with HIV provided a rare opportunity to investigate this.</p> <p>Case Presentation</p> <p>A 30-year-old male was admitted on day 4 of influenza-like-illness with tachycardia, tachypnea, hypoxemia and bilateral pulmonary infiltrates. Influenza A/H5N1 and HIV tests were positive and the patient was treated with Oseltamivir and broad-spectrum antibiotics. Initially his condition improved coinciding with virus clearance by day 6. He clinically deteriorated as of day 10 with fever recrudescence and increasing neutrophil counts and died on day 16. His admission CD4 count was 100/μl and decreased until virus was cleared. CD8 T cells shifted to a CD27⁺CD28^-phenotype. Plasma chemokine and cytokine levels were similar to those found previously in fatal H5N1.</p> <p>Conclusions</p> <p>The course of H5N1 infection was not notably different from other cases. Virus was cleared despite profound CD4 T cell depletion and aberrant CD8 T cell activation but this may have increased susceptibility to a fatal secondary infection.</p

Peak bone mineral density in Vietnamese women

While the prevalence of osteoporosis and risk factors for low bone mineral density (BMD) has been well documented in Caucasian populations, there is a lack of data from Asia. This work was designed to clarify to what extent osteoporosis could be regarded as a major public health problem in Vietnam. Furthermore, to elucidate the prevalence of certain risk factors, such as vitamin D deficiency and other determinants of bone mass as a basis to indentify high-risk individuals among the Vietnamese women and men. The clinical studies were designed as cross-sectional investigations using a multistage sampling scheme. Within the setting of northern Vietnam (latitude 21°N), districts were selected to represent urban and rural areas. In total 612 healthy women and 222 men aged 13-83 years were investigated. BMD was measured at the lumbar spine, femoral neck and total hip in all qualified subjects with dual energy X-ray absortiometry. Serum concentrations of 25(OH)D, parathyroid hormone, estrogen and testosterone were quantified by electrochemiluminescence immunoassay. Data on clinical history and lifestyle were collected by individual face-to-face interviews. Reference values for peak BMD were defined. These data allowed the calculation of T-scores and thus for the first time, an accurate identification of osteoporosis in a Vietnamese population. As determined at the femoral neck, the prevalence of osteoporosis was 17-23% in women and 9% in men. The results clearly suggest that osteoporosis is an important public health problem. Postmenopausal women living in urban areas experienced osteoporosis more than rural residents. Serum levels of 25(OH)D and estrogen were significantly associated with bone mass in both women and men. The prevalence of vitamin D deficiency (<20 ng/mL) was very high, 30% in women and 16% in men. An experimental study on the isoflavone content of different soymilk preparations was performed by HPLC (high pressure liquid chromatography). Values of isoflavones were very low, around 60-80 mg/L, and there were only 10-20% of bioactive aglycones. This is far below the reported threshold levels to exert significant effects on bone. In the future these data will be useful as a valuable reference base to diagnose osteoporosis and for the clinical management of its consequences. The high prevalence of vitamin D deficiency should raise the awareness of potentially important health issues such as osteoporosis but also about other serious diseases within the Vietnamese society