Search results for "bayesian"
showing 10 items of 604 documents
Autonomous ultrasonic inspection using Bayesian optimisation and robust outlier analysis
2020
The use of robotics is beginning to play a key role in automating the data collection process in Non Destructive Testing (NDT). Increasing the use of automation quickly leads to the gathering of large quantities of data, which makes it inefficient, perhaps even infeasible, for a human to parse the information contained in them. This paper presents a solution to this problem by making the process of NDT data acquisition an autonomous one as opposed to an automatic one. In order to achieve this, the robotic data acquisition task is treated as an optimisation problem, where one seeks to find locations with the highest indication of damage. The resulting algorithm combines damage detection tech…
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS
2014
International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…
Gender, Coping, and Mental Health: a Bayesian Network Model Analysis
2016
We examined the relationships among gender, coping, and mental health in terms of probabilities. We selected a sample of university students (N = 131) aged between 18 and 32 years, and used the GHQ-28 and COPE instruments for analysis. The Bayesian network model that we constructed showed higher probabilities of symptoms of mental health problems for emotion-focused coping than for problem-focused coping. No differences were found regarding gender. This suggests that the use of problem-focused coping is more recommendable for both male and female university students, and it may also provide some benefits in terms of treatment of symptoms of mental health problems. However, to further verify…
Possible association between obesity and periodontitis in patients with Down syndrome
2017
Background The present study was carried out to evaluate the possible association between obesity and periodontitis in patients with DS, and to explore which measure of obesity is most closely correlated to periodontitis. Material and Methods A prospective observational study was made to determine whether obesity is related to periodontal disease in patients with DS. The anthropometric variables were body height and weight, which were used to calculate BMI and stratify the patients into three categories: < 25(normal weight), 25-29.9 (overweight) and ≥ 30.0 kg/m2 (obese). Waist circumference and hip circumference in turn was recorded as the greatest circumference at the level of the buttocks…
Active and Secretory IgA-Coated Bacterial Fractions Elucidate Dysbiosis in Clostridium difficile Infection
2016
C. difficile is a major enteric pathogen with worldwide distribution. Its expansion is associated with broad-spectrum antibiotics which disturb the normal gut microbiome. In this study, the DNA sequencing of highly active bacteria and bacteria opsonized by intestinal secretory immunoglobulin A (SIgA) separated from the whole bacterial community by FACS elucidated how the gut dysbiosis promotes C. difficile infection (CDI). Bacterial groups with inhibitory effects on C. difficile growth, such as Lactobacillales, were mostly inactive in the CDI patients. C. difficile was typical for the bacterial fraction opsonized by SIgA in patients with CDI, while Fusobacterium was characteristic for the S…
Genome-scale analysis of evolutionary rate and selection in a fast-expanding Spanish cluster of HIV-1 subtype F1.
2018
Abstract This work is aimed at assessing the presence of positive selection and/or shifts of the evolutionary rate in a fast-expanding HIV-1 subtype F1 transmission cluster affecting men who have sex with men in Spain. We applied Bayesian coalescent phylogenetics and selection analyses to 23 full-coding region sequences from patients belonging to that cluster, along with other 19 F1 epidemiologically-unrelated sequences. A shift in the overall evolutionary rate of the virus, explained by positively selected sites in the cluster, was detected. We also found one substitution in Nef (H89F) that was specific to the cluster and experienced positive selection. These results suggest that fast tran…
The substitution rate of HIV-1 subtypes: a genomic approach
2017
Abstract HIV-1M causes most infections in the AIDS pandemic. Its genetic diversity is defined by nine pure subtypes and more than sixty recombinant forms. We have performed a comparative analysis of the evolutionary rate of five pure subtypes (A1, B, C, D, and G) and two circulating recombinant forms (CRF01_AE and CRF02 AG) using data obtained from nearly complete genome coding sequences. Times to the most recent common ancestor (tMRCA) and substitution rates of these HIV genomes, and their genomic partitions, were estimated by Bayesian coalescent analyses. Genomic substitution rate estimates were compared between the HIV-1 datasets analyzed by means of randomization tests. Significant diff…
Toward a direct and scalable identification of reduced models for categorical processes.
2017
The applicability of many computational approaches is dwelling on the identification of reduced models defined on a small set of collective variables (colvars). A methodology for scalable probability-preserving identification of reduced models and colvars directly from the data is derived—not relying on the availability of the full relation matrices at any stage of the resulting algorithm, allowing for a robust quantification of reduced model uncertainty and allowing us to impose a priori available physical information. We show two applications of the methodology: (i) to obtain a reduced dynamical model for a polypeptide dynamics in water and (ii) to identify diagnostic rules from a standar…
The best strategy for RAS wild-type metastatic colorectal cancer patients in first-line treatment: A classic and Bayesian meta-analysis
2018
Background: At present, there is uncertainty on the best systemic treatment in first-line setting for RAS wild-type (WT) metastatic colorectal cancer (mCRC) patients. Indeed, several chemotherapy and biologics combinations showed an improvement on survival. We performed a systematic review with a pair-wise and bayesan meta-analysis to rank the best strategy for these patients. Methods: A systematic literature search through March 2017 was performed to evaluate the association between several treatment combinations and overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and toxicity rate (TR) in RAS WT mCRC patients. Data were extracted from studies and pooled…