Search results for "pooling"

The merits and limits of pooling data from nuclear power worker studies

2015

Control of dataset bias in combined Affymetrix cohorts of triple negative breast cancer

2014

AbstractHeterogenous subtypes of breast cancer need to be analyzed separately. Pooling of datasets can provide reasonable sample sizes but dataset bias is an important concern. We assembled a combined dataset of 579 Affymetrix microarrays from triple negative breast cancer (TNBC) in Gene Expression Omnibus (GEO) series GSE31519. We developed a method for selecting comparable datasets and to control for the amount of dataset bias of individual probesets.

La mutualisation logistique à la lumière des pratiques dans le secteur de l'édition

2015

The pooling of resources can be used by companies to reduce costs or facilitate their access to a market when they are small. Among the resources that can be pooled are logistics resources. They can take the form of platforms, warehouses, information systems or even relate to means of transport. The pooling of logistical resources is often presented today as a means of reducing the environmental costs linked to transport. Or is that their only goal? Publishing uses this pooling a lot and this use predates the development of environmental concerns in corporate governance. It therefore seemed interesting to us to study how and why these mutualizations are used in the book supply chain. We try…

Pooling of Nasopharyngeal Swab Specimens for SARS-CoV-2 detection by RT-PCR

2020

ABSTRACTSystematic testing of large population groups by RT-PCR is mandatory to Covid-19 case identification and contact tracing in order to minimize the likelyhood of resurgence in contagion. Sample pooling for RT-PCR has been effectively used to detect community transmission of SARS CoV-2. Nevertheless, this procedure may decrease the sensitivity of RT-PCR assays due to specimen dilution. We evaluated the efficacy of this strategy for diagnosis of Covid-19 using a sensitive commercially-available RT-PCR targeting SARS CoV-2 E and RdRp genes in a single reaction. A total of 20 mini-pools containing either 5 (n=10) or 10 (n=10) nasopharyngeal exudates collected in universal transport medium…

Comparison of Studies on Mobile Phone Use and Risk of Tumors

2010

published results of ameta-analysis of studies on mobile phone use and risk of tumors. Intheir analysis, the authors included 23 case-control studies, covering abroad spectrum of tumor entities including uveal melanoma, testicu-lar cancer, parotid gland tumors, and brain tumors.However, the authors give no rationale for pooling these hetero-geneous, biologically rather diverse cancer sites, for which the local-ized exposure from the use of mobile phones is completely different.The key difference between this particular meta-analysis com-pared with earlier ones is the use of a quality score. The use of qualityscoreshasbeenreportedtobea“formofsubjectivitymasqueradingasobjectivity”andithasbeen…

Occupational Exposure to Extremely Low-Frequency Magnetic Fields and Risk of Amyotrophic Lateral Sclerosis : Results of a Feasibility Study for a Poo…

2021

Bioelectromagnetics 42(4), 271-283 (2021). doi:10.1002/bem.22335

Automatic Segmentation Using a Hybrid Dense Network Integrated With an 3D-Atrous Spatial Pyramid Pooling Module for Computed Tomography (CT) Imaging

2020

Computed tomography (CT) with a contrast-enhanced imaging technique is extensively proposed for the assessment and segmentation of multiple organs, especially organs at risk. It is an important factor involved in the decision making in clinical applications. Automatic segmentation and extraction of abdominal organs, such as thoracic organs at risk, from CT images are challenging tasks due to the low contrast of pixel values surrounding other organs. Various deep learning models based on 2D and 3D convolutional neural networks have been proposed for the segmentation of medical images because of their automatic feature extraction capability based on large labeled datasets. In this paper, we p…

Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons

2013

Network meta-analysis techniques allow for pooling evidence from different studies with only partially overlapping designs for getting a broader basis for decision support. The results are network-based effect estimates that take indirect evidence into account for all pairs of treatments. The results critically depend on homogeneity and consistency assumptions, which are sometimes difficult to investigate. To support such evaluation, we propose a display of the flow of evidence and introduce new measures that characterize the structure of a mixed treatment comparison. Specifically, a linear fixed effects model for network meta-analysis is considered, where the network estimates for two trea…

Entry with two correlated signals : the case of industrial espionage and its positive competitive effects

2021

Recent advances in information and communication technologies have increased the incentives for firms to acquire information about rivals. These advances may have major implications for market entry because they make it easier for potential entrants to gather valuable information about, for example, an incumbent’s cost structure. However, little theoretical research has actually analyzed this question. This paper advances the literature by extending a one-sided asymmetric information version of Milgrom and Roberts’ (1982) limit pricing model. Here, the entrant is allowed access to an intelligence system (IS) of a certain precision that generates a noisy signal on the incumbent’s cost struct…

Assessing covariate imbalance in meta-analysis studies.

2010

The main goal of meta-analysis is to combine data across studies or data sets to obtain summary estimates. In this paper, the novelty is to propose a statistical tool to assess a possible covariate imbalance in baseline variables to investigate similarity of trials. We conducted the detection of the covariate imbalance, first, through some graphical comparison of the empirical cumulative distribution functions or ECDFs, which are built by putting together arms or trials according to some risk factor, and second, through some non-parametric tests such as the Kolmogorov–Smirnov and the Anderson–Darling tests. To overcome the huge presence of ties, we conducted the statistical tests on perturbe…