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At least 685 records · Page 38Linked to original sources
PubMed1991

Experiences in data analysis and modelling with a multichannel biomagnetic system.

Evaluation of MEG/MCG data, measured with the Siemens biomagnetic multichannel system KRENIKON, in patients with epilepsy, infarction, Wolff-Parkinson-White (WPW) syndrome or extra systoles are in good agreement with the results of different investigation techniques. The evaluations have been performed using an equivalent current dipole model within a sphere or a half-space with homogeneous conductivity. In cases where the current dipole model is not adequate, multiple dipoles or complete distributions of current sources have to be considered. Results from simulations and applications to in vivo data and the influence of geometries better adjusted to realistic geometries are discussed.

Brain↗
PubMed1998

Center's pain management program revamped thanks to data analysis, tracking.

Take control of costly pain management using a data-driven approach. A QI team at this Wisconsin hospital identified best practices in pain management, then set out to revamp the facility's pain management policy. Here are the details, plus actual forms used and some interesting pain treatment benchmarks from 16 facilities.

Benchmarking↗
PubMed2002

Artificial neural networks for automation of Rutherford backscattering spectroscopy experiments and data analysis.

We present an algorithm based on artificial neural networks able to determine optimized experimental conditions for Rutherford backscattering measurements of Ge-implanted Si. The algorithm can be implemented for any other element implanted into a lighter substrate. It is foreseeable that the method developed in this work can be applied to still many other systems. The algorithm presented is a push-button black box, and does not require any human intervention. It is thus suited for automated control of an experimental setup, given an interface to the relevant hardware. Once the experimental conditions are optimized, the algorithm analyzes the final data obtained, and determines the desired parameters. The method is thus also suited for automated analysis of the data. The algorithm presented can be easily extended to other ion beam analysis techniques. Finally, it is suggested how the artificial neural networks required for automated control and analysis of experiments could be automatically generated. This would be suited for automated generation of the required computer code. Thus could RBS be done without experimentalists, data analysts, or programmers, with only technicians to keep the machines running.

Journal Article↗
PubMed2003

[Prevalence of diabetes mellitus in Germany 1998-2001. Secondary data analysis of a health insurance sample of the AOK in Hesse/KV in Hesse].

AIMS: The aim of this population-based study was to assess the prevalence of subjects with diabetes mellitus by retrospectively analysing routine health insurance data. METHODS: This analysis comprised a 18.75% random sample of all members of the largest regional statutory health insurance (Allgemeine Ortskrankenkasse, AOK) in Hesse. Patients with diabetes were identified by criteria such as ICD-10 diagnoses and regular prescriptions of insulin and oral antidiabetic agents. The data were corrected for the age and gender distribution of the German population. RESULTS: Over the 4-year observation period there was a continuous increase in the prevalence of subjects with known diabetes mellitus, from 7.24% in 1998 to 8.79% in 2001. After correction for the German population the last figure corresponded to a prevalence rate of 6.00% in 1998 and 6.91% in 2001. During this period, there was an overproportional increase in the percentage of subjects treated with insulin, from 1.49% in 1998 to 1.91% in 2001, while there was only a moderate increase in the percentage of subjects under oral medication and under dietary treatment, respectively. In the age group of 70 and above roughly 25% of all subjects had known diabetes. In this age group, more than 6% of all people were treated with insulin. CONCLUSIONS: This data suggests that there was a continuous increase in the prevalence of individuals treated for diabetes between 1998 and 2001 in Germany by approximately 5% per year. After correction for the total German population the pre-valence of diagnosed diabetes is nearly 7%.

Adolescent↗
PubMed2006

Bayesian fMRI data analysis with sparse spatial basis function priors.

In previous work we have described a spatially regularised General Linear Model (GLM) for the analysis of brain functional Magnetic Resonance Imaging (fMRI) data where Posterior Probability Maps (PPMs) are used to characterise regionally specific effects. The spatial regularisation is defined over regression coefficients via a Laplacian kernel matrix and embodies prior knowledge that evoked responses are spatially contiguous and locally homogeneous. In this paper we propose to finesse this Bayesian framework by specifying spatial priors using Sparse Spatial Basis Functions (SSBFs). These are defined via a hierarchical probabilistic model which, when inverted, automatically selects an appropriate subset of basis functions. The method includes non-linear wavelet shrinkage as a special case. As compared to Laplacian spatial priors, SSBFs allow for spatial variations in signal smoothness, are more computationally efficient and are robust to heteroscedastic noise. Results are shown on synthetic data and on data from an event-related fMRI experiment.

Algorithms↗
PubMed1995

[Strategies for data analysis of brain activation studies with functional MR tomography].

The sensitivity of gradient-echo magnetic resonance imaging (MRI) to changes in cerebral blood oxygenation has been introduced for mapping functional brain activation. To benefit from the high spatial and temporal resolution of the respective dynamic MRI data sets, their analysis requires algorithms that are capable of both precisely delineating task-related activation patterns and demonstrating functional connectivity of interacting areas. Here, we present various strategies for data evaluation by means of correlational analyses that surpass the quality of subtraction-based activation maps by improving both sensitivity and robustness. On a pixel-by-pixel basis the approach correlates signal time courses with a reference function, reflecting the temporal sequence of activated and control states. Extended versions employ the calculation of auto- or cross-correlation functions that increase sensitivity, but require periodic stimulations. Following individual correction for non-specific but correlated signal fluctuations, mapping of task-related coherent activation can be improved using neighborhood principles. Such refined strategies are expected to enhance the usefulness of oxygenation-sensitive MRI for studying the functional anatomy of the human brain under both physiological and pathological conditions.

Algorithms↗
PubMed2003

Pedigree data analysis with crossover interference.

We propose a new method for calculating probabilities for pedigree genetic data that incorporates crossover interference using the chi-square models. Applications include relationship inference, genetic map construction, and linkage analysis. The method is based on importance sampling of unobserved inheritance patterns conditional on the observed genotype data and takes advantage of fast algorithms for no-interference models while using reweighting to allow for interference. We show that the method is effective for arbitrarily many markers with small pedigrees.

Algorithms↗
PubMed2004

POSA: perl objects for DNA sequencing data analysis.

BACKGROUND: Capillary DNA sequencing machines allow the generation of vast amounts of data with little hands-on time. With this expansion of data generation, there is a growing need for automated data processing. Most available software solutions, however, still require user intervention or provide modules that need advanced informatics skills to allow implementation in pipelines. RESULTS: Here we present POSA, a pair of new perl objects that describe DNA sequence traces and Phrap contig assemblies in detail. Methods included in POSA include basecalling with quality scores (by Phred), contig assembly (by Phrap), generation of primer3 input and automated SNP annotation (by PolyPhred). Although easily implemented by users with only limited programming experience, these objects considerabily reduce hands-on analysis time compared to using the Staden package for extracting sequence information from raw sequencing files and for SNP discovery. CONCLUSIONS: The POSA objects allow a flexible and easy design, implementation and usage of perl-based pipelines to handle and analyze DNA sequencing data, while requiring only minor programming skills.

Contig Mapping↗
PubMed1996

A comparison of statistical methods for clustered data analysis with Gaussian error.

We investigate by simulation the properties of four different estimation procedures under a linear model for correlated data with Gaussian error: maximum likelihood based on the normal mixed linear model; generalized estimating equations; a four-stage method, and a bootstrap method that resamples clusters rather than individuals. We pay special attention to the group randomized trials where the number of independent clusters is small, cluster sizes are big, and the correlation within the cluster is weak. We show that for balanced and near balanced data when the number of independent clusters is small (< or = 10), the bootstrap is superior if analysts do not want to impose strong distribution and covariance structure assumptions. Otherwise, ML and four-stage methods are slightly better. All four methods perform well when the number of independent clusters reaches 50.

Bias↗
PubMed2003

GEPAS: A web-based resource for microarray gene expression data analysis.

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).

Cluster Analysis↗
PubMed1999

A graphic orientated data analysis system for hemodynamic research.

A software program to process and to extract physiological functional hemodynamics data has been developed and reported. The purpose of this software system is to process and capture cardiovascular hemodynamics and physiological functional data after data acquisition. The system utilized an interactive graphic display and script control to extract the data. With a minimum interface, it is capable of analyzing multiple channels of data and simultaneously obtaining the results. The extracted data includes global cardiovascular functional parameters and with script process the software will calculate stroke work from the pressure length relationship. The results are stored in files for further statistical analysis. The procedures are reliable and readily applicable to examine and analyze the acquired data with minimal observer bias.

Computer Graphics↗
PubMed1983

A computer-based data analysis system for enzyme-linked immunosorbent assays.

A computerized system is presented for automating the data collection, processing, and displaying tasks involved in enzyme-linked immunosorbent assays. This system uses a through-the-well absorbance reader of microtiter plates interfaced to a minicomputer running the UNIX operating system. Optical density in each well of a 96-well microtiter plate is recorded as a function of time for up to 10 time points. These data are automatically transmitted to the remote computer. The rate of product formation is then calculated for each well, and a battery of analysis, display, and comparison programs can then be used by the researcher for data presentation. Using the initial rate of reaction as the basis for quantifying enzyme-linked immunosorbent assays focuses on the catalytic property of the enzyme and allows a large dynamic range of the assay on any plate. These programs can be adapted to virtually any mini- or microcomputer with a graphics display or a plotting device. Assuming moderately powerful computing hardware, throughputs of 50 plates per day are easily achieved. The programs work equally well with peroxidase, beta-galactosidase, or alkaline phosphatase conjugated second antibodies, and with whole cell or soluble antigens.

Antibodies, Monoclonal↗
PubMed2004

Challenges of building clinical data analysis solutions.

Increasingly, owners of clinical information systems are turning to clinical data warehouses (CDWs) to store and to analyze their data. The CDW allows institutions to make better use of their clinical data that has been collected through its information systems. A CDW extracts data from these systems, transforms it into a usable form, and then allows users to view and analyze years of data across a large cross section of patient charts. Although warehouses have existed in healthcare for some time, there are relatively few institutions that maintain patient charts in a CDW. This is, in part, because of the challenges often seen when attempting to warehouse this type of data. These include integrating a diverse set of care practices and a variety of definitions for common data elements like medications, observations, treatments, units of measure, and even unique patient identifiers. In addition, these systems often struggle with a high level of inconsistent and/or incomplete data that must be cleaned up on a regular basis. Unlike other data warehouse systems, CDWs are often expected to gather data around the clock and in a manner that has minimum impact to the performance of the source Clinical Information Systems. Finally, CDWs often have a diverse range of clinical and administrative users. This often leads to a need for a variety of applications and/or tools for viewing and analyzing the data.

Database Management Systems↗
PubMed2002

SeaWiFs satellite data analysis of Black Sea water discharge pattern into the Aegean Sea.

Satellite data from the SeaWiFS sensor has been used to determine chlorophyll-a contents in the North Aegean Sea using SEADAS 3.3 software. The data is used to extract knowledge on water movements/flow phenomena using chlorophyll as a "tracer" but will also indicate water quality. More than 100 SeaWiFS scenes from 1998 up to 2001 have been analyzed in terms of hydrodynamic phenomena, mainly the transport and spreading pattern of Black Sea Water in the North Aegean Sea but also concerning the water quality and its seasonal and yearly variation at the mouth region of the Dardanelles. Some comparison with earlier studies using NOAA AVHRR thermal data and historical CZCS scenes is also made.

Baltic States↗