437 research outputs found
The IBMAP approach for Markov networks structure learning
In this work we consider the problem of learning the structure of Markov
networks from data. We present an approach for tackling this problem called
IBMAP, together with an efficient instantiation of the approach: the IBMAP-HC
algorithm, designed for avoiding important limitations of existing
independence-based algorithms. These algorithms proceed by performing
statistical independence tests on data, trusting completely the outcome of each
test. In practice tests may be incorrect, resulting in potential cascading
errors and the consequent reduction in the quality of the structures learned.
IBMAP contemplates this uncertainty in the outcome of the tests through a
probabilistic maximum-a-posteriori approach. The approach is instantiated in
the IBMAP-HC algorithm, a structure selection strategy that performs a
polynomial heuristic local search in the space of possible structures. We
present an extensive empirical evaluation on synthetic and real data, showing
that our algorithm outperforms significantly the current independence-based
algorithms, in terms of data efficiency and quality of learned structures, with
equivalent computational complexities. We also show the performance of IBMAP-HC
in a real-world application of knowledge discovery: EDAs, which are
evolutionary algorithms that use structure learning on each generation for
modeling the distribution of populations. The experiments show that when
IBMAP-HC is used to learn the structure, EDAs improve the convergence to the
optimum
A Comparison of MCMC Sampling for Probabilistic Logic Programming
Markov Chain Monte Carlo (MCMC) methods are a class of algorithms used to perform approximate inference in probabilistic models. When direct sampling from a probability distribution is difficult, MCMC algorithms provide accurate results by constructing a Markov chain that gradually approximates the desired distribution. In this paper we describe and compare the performances of two MCMC sampling algorithms, Gibbs sampling and Metropolis Hastings sampling, with rejection sampling for probabilistic logic programs. In particular, we analyse the relation between execution time and number of samples and how fast each algorithm converges
Development of a clockwork light source to enable cervical inspection by village health workers
BACKGROUND: Cervical cancer can often be prevented by screening and may be curable if identified and treated in its early stages. However, 80% of new cases occur in less-developed countries where cervical cancer screening programmes are small-scale or non-existent. This is a human tragedy of great proportion, with many of those affected being young mothers. There is some evidence that cancerous or precancerous lesions may be detected by visual inspection with acetic acid (VIA) and field studies indicate that this technique is effective, safe and acceptable to women. However, the provision of a light source for inspection of the cervix presents a major problem in less-developed countries, where candles and torches often provide the only means of illumination. Our objective was to develop a light source based on clockwork technology, that required no batteries or external power source. METHODS: We adapted the design of a commercially available clockwork torch to provide a light source for cervical inspection. The light source was then tested under laboratory conditions in a comparison with other illumination methods typically used in this application. RESULTS: The light source gave illuminance levels greater than those produced by any other method tested, and also had considerable advantages in terms of ease of use and safety. CONCLUSION: This design is small, compact, effective and safe to use and promises a better and more affordable means of visualising the cervix. Further field trials of VIA are now required which incorporate this light source
'What was your blood sugar reading this morning?': representing diabetes self-management on Facebook
Social networking sites have swiftly become a salient venue for the production and consumption of neoliberal health discourse by individuals and organisations. These platforms offer both opportunities for individuals to accrue coping resources and a means for organisations to promote their agendas to an online audience. Focusing specifically on diabetes, this article examines the representation of social actors and interactional styles on three organisational Pages on Facebook. Drawing on media and communication theories, we situate this linguistic analysis in relation to the communicative affordances employed by these organisations as they publish content online. Diabetes sufferers are represented as an at-risk group whose vulnerabilities can be managed through forms of participation specific to the respective organisation. More popular diabetes Pages draw on the opportunities for social interaction afforded by Facebook and combine informational and promotional content to foster communication between the organisation and its audience. By encouraging reflexive management of diabetes risks, these Pages contribute to the construction of âbiological citizensâ who interweave habitual interactions on social networking sites with responsible self-care, consumption of health information and health activism
Detection of regulator genes and eQTLs in gene networks
Genetic differences between individuals associated to quantitative phenotypic
traits, including disease states, are usually found in non-coding genomic
regions. These genetic variants are often also associated to differences in
expression levels of nearby genes (they are "expression quantitative trait
loci" or eQTLs for short) and presumably play a gene regulatory role, affecting
the status of molecular networks of interacting genes, proteins and
metabolites. Computational systems biology approaches to reconstruct causal
gene networks from large-scale omics data have therefore become essential to
understand the structure of networks controlled by eQTLs together with other
regulatory genes, and to generate detailed hypotheses about the molecular
mechanisms that lead from genotype to phenotype. Here we review the main
analytical methods and softwares to identify eQTLs and their associated genes,
to reconstruct co-expression networks and modules, to reconstruct causal
Bayesian gene and module networks, and to validate predicted networks in
silico.Comment: minor revision with typos corrected; review article; 24 pages, 2
figure
Use of the internet by Italian pediatricians: habits, impact on clinical practice and expectations
<p>Abstract</p> <p>Background</p> <p>Medical professionals go online for literature searches and communication with families.</p> <p>We administered a questionnaire to members of the Italian Society of Pediatrics to assess determinants of their use of the Internet, of social platforms and of personal health records during clinical practice.</p> <p>Methods</p> <p>All the 9180 members of the Italian Society of Pediatrics were invited to fill in a questionnaire concerning use of the Internet and usefulness of Internet-based tools during clinical practice. The questionnaire was administered through the SurveyMonkey<sup>Âź </sup>web platform. Logistic regression analysis was used to study factors affecting use and influence of the Internet in clinical practice.</p> <p>Results</p> <p>A total of 1335 (14.5%) members returned the questionnaire. Mean age was 49.2 years, 58.6% were female. 32.3% had access to the Internet through a Smartphone. 71.9% of respondents used the Internet during clinical practice, mainly searching for guidelines and drug references. Use of the Internet during clinical practice was more frequent among younger pediatricians (OR 0.964; 95% CI 0.591-0.978), males (OR 1.602; 95% CI 1.209-2.123) and those living in Northern and Central Italy (OR 1.441; 95% CI 1.111-1.869), while it was lower among family pediatricians. 94.6% of respondents were influenced in their clinical practice by information found on the Internet, in particular younger pediatricians (OR 0.96, 95% CI 0.932-0.989), hospital pediatricians (OR 2.929, 95% CI 1.708-5.024), and other pediatric profiles (OR 6.143, 95%CI 1.848-20.423). 15.9% of respondents stated that social networks may be useful in pediatric practice. Slightly more than half (50.5%) of respondents stated that personal health records may be clinically relevant. Registrars and hospital pediatricians were more likely to perceive personal health records as useful tools for clinical practice. Additional resources pediatricians would like to access were free bibliographic databases and tools for interacting with families.</p> <p>Conclusions</p> <p>Italian pediatricians frequently use the Internet during their practice. One-third of them access the Internet through a Smartphone. Interaction with families and their empowerment can be improved by the use of Internet tools, including personal health records, toward which respondents show a significant interest. Though, they show a general resistance to the introduction of social networks in clinical practice.</p
Maternal educational level, parental preventive behavior, risk behavior, social support and medical care consumption in 8-month-old children in Malmö, Sweden
<p>Abstract</p> <p>Background</p> <p>The social environment in which children grow up is closely associated with their health. The aim of this study was to investigate the relationship between maternal educational level, parental preventive behavior, parental risk behavior, social support, and use of medical care in small children in Malmö, Sweden. We also wanted to investigate whether potential differences in child medical care consumption could be explained by differences in parental behavior and social support.</p> <p>Methods</p> <p>This study was population-based and cross-sectional. The study population was 8 month-old children in Malmö, visiting the Child Health Care centers during 2003-2007 for their 8-months check-up, and whose parents answered a self-administered questionnaire (n = 9,289 children).</p> <p>Results</p> <p>Exclusive breast feeding â„4 months was more common among mothers with higher educational level. Smoking during pregnancy was five times more common among less-educated mothers. Presence of secondhand tobacco smoke during the first four weeks of life was also much more common among children with less-educated mothers. Less-educated mothers more often experienced low emotional support and low practical support than mothers with higher levels of education (>12 years of education). Increased exposure to unfavorable parental behavioral factors (maternal smoking during pregnancy, secondhand tobacco smoke and exclusive breastfeeding <4 months) was associated with increased odds of in-hospital care and having sought care from a doctor during the last 8 months. The odds were doubled when exposed to all three risk factors. Furthermore, children of less-educated mothers had increased odds of in-hospital care (OR = 1.34 (95% CI: 1.08, 1.66)) and having sought care from a doctor during the last 8 months (OR = 1.28 (95% CI: 1.09, 1.50)), which were reduced and turned statistically non-significant after adjustment for unfavorable parental behavioral factors.</p> <p>Conclusion</p> <p>Children of less-educated mothers were exposed to more health risks, fewer health-promoting factors, worse social support, and had higher medical care consumption than children with higher educated mothers. After adjustment for parental behavioral factors the excess odds of doctor's visits and in-hospital care among children with less-educated mothers were reduced. Improving children's health calls for policies targeting parents' health-related behaviors and social support.</p
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