982 resultados para meta-learning
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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
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Calcium is vital to the normal functioning of multiple organ systems and its serum concentration is tightly regulated. Apart from CASR, the genes associated with serum calcium are largely unknown. We conducted a genome-wide association meta-analysis of 39,400 individuals from 17 population-based cohorts and investigated the 14 most strongly associated loci in ≤ 21,679 additional individuals. Seven loci (six new regions) in association with serum calcium were identified and replicated. Rs1570669 near CYP24A1 (P = 9.1E-12), rs10491003 upstream of GATA3 (P = 4.8E-09) and rs7481584 in CARS (P = 1.2E-10) implicate regions involved in Mendelian calcemic disorders: Rs1550532 in DGKD (P = 8.2E-11), also associated with bone density, and rs7336933 near DGKH/KIAA0564 (P = 9.1E-10) are near genes that encode distinct isoforms of diacylglycerol kinase. Rs780094 is in GCKR. We characterized the expression of these genes in gut, kidney, and bone, and demonstrate modulation of gene expression in bone in response to dietary calcium in mice. Our results shed new light on the genetics of calcium homeostasis.
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The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.
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The application of support vector machine classification (SVM) to combined information from magnetic resonance imaging (MRI) and [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) has been shown to improve detection and differentiation of Alzheimer's disease dementia (AD) and frontotemporal lobar degeneration. To validate this approach for the most frequent dementia syndrome AD, and to test its applicability to multicenter data, we randomly extracted FDG-PET and MRI data of 28 AD patients and 28 healthy control subjects from the database provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and compared them to data of 21 patients with AD and 13 control subjects from our own Leipzig cohort. SVM classification using combined volume-of-interest information from FDG-PET and MRI based on comprehensive quantitative meta-analyses investigating dementia syndromes revealed a higher discrimination accuracy in comparison to single modality classification. For the ADNI dataset accuracy rates of up to 88% and for the Leipzig cohort of up to 100% were obtained. Classifiers trained on the ADNI data discriminated the Leipzig cohorts with an accuracy of 91%. In conclusion, our results suggest SVM classification based on quantitative meta-analyses of multicenter data as a valid method for individual AD diagnosis. Furthermore, combining imaging information from MRI and FDG-PET might substantially improve the accuracy of AD diagnosis.
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BACKGROUND: The early detection of medullary thyroid carcinoma (MTC) can improve patient prognosis, because histological stage and patient age at diagnosis are highly relevant prognostic factors. As a consequence, delay in the diagnosis and/or incomplete surgical treatment should correlate with a poorer prognosis for patients. Few papers have evaluated the specific capability of fine-needle aspiration cytology (FNAC) to detect MTC, and small series have been reported. This study conducts a meta-analysis of published data on the diagnostic performance of FNAC in MTC to provide more robust estimates. RESEARCH DESIGN AND METHODS: A comprehensive computer literature search of the PubMed/MEDLINE, Embase and Scopus databases was conducted by searching for the terms 'medullary thyroid' AND 'cytology', 'FNA', 'FNAB', 'FNAC', 'fine needle' or 'fine-needle'. The search was updated until 21 March 2014, and no language restrictions were used. RESULTS: Fifteen relevant studies and 641 MTC lesions that had undergone FNAC were included. The detection rate (DR) of FNAC in patients with MTC (diagnosed as 'MTC' or 'suspicious for MTC') on a per lesion-based analysis ranged from 12·5% to 88·2%, with a pooled estimate of 56·4% (95% CI: 52·6-60·1%). The included studies were statistically heterogeneous in their estimates of DR (I-square >50%). Egger's regression intercept for DR pooling was 0·03 (95% CI: -3·1 to 3·2, P = 0·9). The study that reported the largest MTC series had a DR of 45%. Data on immunohistochemistry for calcitonin in diagnosing MTC were inconsistent for the meta-analysis. CONCLUSIONS: The presented meta-analysis demonstrates that FNAC is able to detect approximately one-half of MTC lesions. These findings suggest that other techniques may be needed in combination with FNAC to diagnose MTC and avoid false negative results.
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Objective: Resection of lung metastases (LM) from colorectal cancer (CRC)¦is increasingly performed with a curative intent.Most series report small groups¦of patients, and it is currently not possible to identify those CRC patients who¦may benefit the most of surgical management. It is clinically relevant to assess¦risk factors for prolonged survival after this type of procedures.¦Methods: A meta analysis of 24 series published between 2000 and 2011¦which focused on surgical management of LM from CRC and included more¦than 40 patients each, with or without prior resection of in transit liver¦metastases. Random effects were calculated for five variables considered as¦potential prognostic factors.¦Results: A total of 2815 patients who underwent surgery with a curative¦intent were considered in this analysis. Four parameters were associated with¦a decreased survival: 1) a short disease-free interval between primary tumor¦resection and development of LM (HR = 1·59, 95% CI 1·27-1·98); 2) multiple¦LM (HR = 2·04, 95%CI 1·72-2·41); 3) positive hilar/mediastinal lymph nodes¦(HR = 1·65, 95% CI 1·35-2·02); and 4) a high prethoracotomy CEA value (HR¦=1·91, 95% CI 1·57-2·32). By comparison, a history of resected liver metastases¦(HR = 1·36, 95% CI 0·92-2·03) did not achieve statistical significance.¦Conclusion: Risk factors for poor clinical outcome after surgery for lung¦metastases in CRC patients include: 1) synchronous lung metastases; 2) high¦pre-thoracotomy CEA; 3) hilar nodes involvement; and 4) multiple pulmonary¦lesions.
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Evidence Review 4 - Adult learning services Briefing 4 - Adult learning services This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of participation in learning as an adult in improving health. There is evidence that involvement in adult learning has both direct and indirect links with health, for example because it increases employability. There is some evidence that those who are lower down the social gradient benefit most, in health terms, from adult learning. However, there is a gradient both in participation in adult learning and skill level, whereby the more someone would benefit from adult learning, the less likely they are to participate, and the lower their literacy and numeracy skills are likely to be. This is due to a range of barriers, including prohibitively high costs, lack of personal confidence, or lack of availability and access. These papers also show that there are a number of actions local authorities can take to increase access to adult learning, improve quality of provision and increase the extent to which it is delivered and targeted proportionate to need. The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.
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Substance use behaviors of young people attending a special school are reported over a 4-year period from the age of 12-16 years. The article investigated these behaviors by surveying a cohort of young people with a statement for moderate learning disabilities annually during the last 4 years of compulsory schooling. The findings show that these young people consistently reported lower levels of tobacco, alcohol, and cannabis use compared with those attending mainstream school. No other illicit drug use was reported. The potential implications of these findings are discussed in relation to the context and timing of targeted substance education and prevention initiatives for young people with moderate learning disability attending a special school.This resource was contributed by The National Documentation Centre on Drug Use.
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While dementia affects 6-10% of persons 65 years or older, industrialized countries have witnessed an alarming rise in obesity. However, obesity's influence on dementia remains poorly understood. The conducted a systematic review and meta-analysis. PUBMED search (1995-2007) resulted in 10 relevant prospective cohort studies of older adults (40-80 years at baseline) with end points being dementia and predictors including adiposity measures, such as body mass index (BMI) and waist circumference (WC). There was a significant U-shaped association between BMI and dementia (P= 0.034), with dementia risk increased for obesity and underweight. Pooled odds ratios (OR) and 95% confidence intervals (CI) for underweight, overweight and obesity compared with normal weight in relation to incident dementia were: 1.36 (1.07, 1.73), 0.88 (0.60, 1.27) and 1.42 (0.93, 2.18) respectively. Pooled ORs and 95% CI for obesity and incident Alzheimer's disease (AD) and vascular dementia were 1.80 (1.00, 3.29) vs. 1.73 (0.47, 6.31) and were stronger in studies with long follow-up (>10 years) and young baseline age (
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Background: A form of education called Interprofessional Education (IPE) occurs when two or more professions learn with, from and about each other. The purpose of IPE is to improve collaboration and the quality of care. Today, IPE is considered as a key educational approach for students in the health professions. IPE is highly effective when delivered in active patient care, such as in clinical placements. General internal medicine (GIM) is a core discipline where hospital-based clinical placements are mandatory for students in many health professions. However, few interprofessional (IP) clinical placements in GIM have been implemented. We designed such a placement. Placement design: The placement took place in the Department of Internal Medicine at the CHUV. It involved students from nursing, physiotherapy and medicine. The students were in their last year before graduation. Students formed teams consisting of one student from each profession. Each team worked in the same unit and had to take care of the same patient. The placement lasted three weeks. It included formal IP sessions, the most important being facilitated discussions or "briefings" (3x/w) during which the students discussed patient care and management. Four teams of students eventually took part in this project. Method: We performed a type of evaluation research called formative evaluation. This aimed at (1) understanding the educational experience and (2) assessing the impact of the placement on student learning. We collected quantitative data with pre-post clerkship questionnaires. We also collected qualitative data with two Focus Groups (FG) discussions at the end of the placement. The FG were audiotaped and transcribed. A thematic analysis was then performed. Results: We focused on the qualitative data, since the quantitative data lacked of statistical power due to the small numbers of students (N = 11). Five themes emerged from the FG analysis: (1) Learning of others' roles, (2) Learning collaborative competences, (3) Striking a balance between acquiring one's own professional competences and interprofessional competences, (4) Barriers to apply learnt IP competences in the future and (5) Advantages and disadvantages of IP briefings. Conclusions: Our IP clinical placement in GIM appeared to help students learn other professionals' roles and collaborative skills. Some challenges (e.g. finding the same patient for each team) were identified and will require adjustments.
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The prevalence of obesity is rapidly increasing in older adults. Information is required about what interventions are effective in reducing obesity and influencing health outcomes in this age group. Thirteen databases were searched, earliest date 1966 to December 2008, including Medline, CINAHL, PsycINFO, the Cochrane database and EMBASE.
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Purpose: the prevalence of obesity is rapidly increasing in older adults. Information is required about what interventions are effective in reducing obesity and influencing health outcomes in this age group. Design: systematic review and meta-analysis. Data sources: thirteen databases were searched, earliest date 1966 to December 2008, including Medline, CINAHL, PsycINFO, the Cochrane database and EMBASE. Study selection: we included studies with participants�۪ mean age 60 years and mean body mass index 30 kg/m2, with outcomes at a minimum of 1 year. Data were independently extracted by two reviewers and differences resolved by consensus. Data extraction: nine eligible trials were included. Study interventions targeted diet, physical activity and mixed approaches. Populations included patients with coronary artery disease, diabetes mellitus and osteoarthritis. Results: meta-analysis (seven studies) demonstrated a modest but significant weight loss of 3.0 kg [95% confidence interval (CI) 5.1���0.9] at 1 year. Total cholesterol (four studies) did not show a significant change: ���0.36 mmol/l (95% CI ���0.75 to 0.04). There was no significant change in high-density lipoprotein, low-density lipoprotein or triglycerides. In one study, recurrence of hypertension or cardiovascular events was significantly reduced (hazard ratio 0.65, 95% CI 0.50���0.85). Six-minute walk test did not significantly change in one study. Health-related quality of life significantly improved in one study but did not improve in a second study. Conclusions: although modest weight reductions were observed, there is a lack of high-quality evidence to support the efficacy of weight loss programmes in older people. ��Keywords: obesity, older, weight loss, meta-analysis, elderly, systematic review