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At least 1,279 records · Page 71Linked to original sources
PubMed2001

Implementation of an integrated instrument control and data management system for point of care blood gas testing.

Critical care testing in a point of care (POC) setting can be very demanding for the laboratory. Lack of continuous monitoring of the normal functioning of POC instruments leads to late response to technical problems, and frequently results in more comprehensive interventions and reduced instrument availability. As most POC instruments lack adequate data transfer capabilities, manual data entry into the medical records with a high error rate is a component of POC programs. To reduce this data handling drawback of POC testing, our hospital opted for the replacement of the existing analysers with network-ready, expandable analysers (ABL700), linked to an integrated management system (RADIANCE). This new set-up enabled us to have continuous instrument control and maximal data management. The implementation of the integrated management system was well accepted by the operators. The network connectivity has led to real time technical support while reducing the workload by automating data collection.

Blood Gas Analysis↗
PubMed2005

KaPPA-view: a web-based analysis tool for integration of transcript and metabolite data on plant metabolic pathway maps.

The application of DNA array technology and chromatographic separation techniques coupled with mass spectrometry to transcriptomic and metabolomic analyses in plants has resulted in the generation of considerable quantitative data related to transcription and metabolism. The integration of "omic" data is one of the major concerns associated with research into identifying gene function. Thus, we developed a Web-based tool, KaPPA-View, for representing quantitative data for individual transcripts and/or metabolites on plant metabolic pathway maps. We prepared a set of comprehensive metabolic pathway maps for Arabidopsis (Arabidopsis thaliana) and depicted these graphically in Scalable Vector Graphics format. Individual transcripts assigned to a reaction are represented symbolically together with the symbols of the reaction and metabolites on metabolic pathway maps. Using quantitative values for transcripts and/or metabolites submitted by the user as Comma Separated Value-formatted text through the Internet, the KaPPA-View server inserts colored symbols corresponding to a defined metabolic process at that site on the maps and returns them to the user's browser. The server also provides information on transcripts and metabolites in pop-up windows. To demonstrate the process, we describe the dataset obtained for transgenic plants that overexpress the PAP1 gene encoding a MYB transcription factor on metabolic pathway maps. The presentation of data in this manner is useful for viewing metabolic data in a way that facilitates the discussion of gene function.

Computational Biology↗
PubMed1977

An integrated medical record and data system for primary care. Part 1: the age-sex register: definition of the patient population.

This is the first of series of articles which describes an integrated system for recording medical data. The age-sex register is described in detail. Uses of the register include enhanced capabilities for office management, assessment of postgraduate educational needs, outreach, audit, and research. The problems encountered with definition of the practice size are discussed. Subsequent articles will describe a classification of health problems, a diagnostic index, family folders, filing patients records by geographic location, problem-oriented medical records, encounter forms, and various record forms.

Age Factors↗
PubMed2026

Integrating plant phenotypic and genotypic data in the AGENT project: a BrAPI service implementation.

MOTIVATION: The AGENT project established a network of actively cooperating European genebanks, integrating genomic and phenotypic data from accessions of wheat and barley. Due to specific storage demands for phenotypic and genotypic data, the project used separate database instances and backend technologies to manage integrated phenotypic and genotypic data. RESULTS: We discuss the challenges encountered when integrating dispersed data to serve through a single interface such as the Plant Breeding Application Programming Interface, BrAPI. We examine how the consistent mappability of genebank data to the BrAPI model can enable the implementation of effective services. The advantages of BrAPI in transparently linking distributed data entities through embedded, unique identifiers are highlighted. We present a technical solution involving a BrAPI proxy, which combines and merges separate BrAPI endpoints. Finally, we demonstrate the AGENT BrAPI implementation with an illustrative example that validates a suggested SNP for a trait from the literature by linking phenotypic, genotypic and passport data. AVAILABILITY AND IMPLEMENTATION: The BrAPI proxy implementation and documentation is available at the Python Package Index (https://pypi.org/project/brapi-proxy) and archived in Zenodo (doi: 10.5281/zenodo.19436445). SUPPLEMENTARY INFORMATION: A Jupyter Notebook file for the validation example using a marker-trait relationship found in the literature.

Phenotype↗
PubMed1997

Automated cardiac output measurement by spatiotemporal integration of color Doppler data. In vitro and clinical validation.

BACKGROUND: A new Doppler echocardiographic technique has been developed for automated cardiac output measurement (ACOM) that assumes neither a flat flow profile nor collinearity with the scan line, but clinical validation of this method is lacking. METHODS AND RESULTS: In 165 subjects (50 intensive care patients, 10 dobutamine echocardiography patients, and 105 normal volunteers; age, 49.4 +/- 19.3 years; 92 men), ACOM was performed in the left ventricular outflow tract (LVOT), with the color baseline shifted to avoid aliasing. ACOM was also tested in a pulsatile in vitro model. Stroke volume was calculated by double integration of Doppler signals in space (across the LVOT) and in time (through the systolic period), assuming hemiaxial symmetry: integral of integral of pi r v(r,t) dr dt, where v(r,t) is the velocity at a distance r from the center of the LVOT at time t during systole. Stroke volume from ACOM was compared with thermodilution (TD), aortic valve pulsed-wave Doppler (PWAO), and left ventricular echocardiographic (two-dimensional [2D]) methods. There was good correlation between ACOM and PWAO (r = .93). TD (r = .86), and 2D (r = .74), with close agreement seen. ACOM had higher correlation and agreement with TD than did either PWAO (P < .02) or 2D (P < .01). ACOM was also able to track accurately the changes in cardiac output with dobutamine infusion in comparison with PWAO (r = .94). In vitro assessment demonstrated excellent correlation (r = .98, y = 1.0x + 1.94) with little impact of pulse repetition frequency or misalignment up to 30 degrees. Gain dependency was noted but could be optimized by visual inspection of the color image. CONCLUSIONS: Automatic integration of numerical data within color Doppler flow fields is a feasible new method for quantifying flow. It is simpler and faster, requires fewer assumptions, and uses only one apical view. ACOM is a promising new approach to echocardiographic quantification that deserves further study and refinement.

Adolescent↗
PubMed1999

Effectiveness of an information broker service.

The many disparate databases existing within the same health care organization create confusion and frustration for the consumer trying to get integrated information. The purpose of this research was to create a regional service that would provide a customer oriented information broker service with a single point of contact and guaranteed performance. From 1/98-6/99 there were 34 requests made. 23 were completed on time, eight still in progress and three were late (86.46% on time, average late time 0.76 days). 13 clinical departments used the service. Data was integrated from twelve different data sources. The requests produced about 2 Gigabytes of integrated data (416,666 single spaced pages). The resources required were approximately 1.3 FTE ($65K in direct costs). The cost/page of integrated information was 19 cents. The benefit to cost ratio was at least 3 and most likely higher. Surveys of customers indicated high satisfaction with services and would both utilize the service again and recommend it to others.

Commerce↗
PubMedDate not supplied

Nurses' integration of outcomes assessment data into practice.

The purpose of this article is to provide initial insight from rational and phenomenologic theoretical perspectives into how nurses integrate baseline and follow-up outcomes assessment data into practice to inform their clinical decision-making. Preliminary findings from 29 nurse interviews indicate that some nurses use outcomes assessment data for evaluating their interventions and for decisions concerning initial and/or discharge planning. Nurses' perceived usefulness of outcomes data was based on task complexity and nurses' level of expertise.

Attitude of Health Personnel↗
PubMed2005

ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.

SUMMARY: ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics (SVG). Deciphering the crosstalk among pathways and integrating biomedical ontologies and knowledge bases may help biological interpretation of microarray data. ArrayXPath is empowered by integrating gene-pathway, disease-pathway, drug-pathway and pathway-pathway correlations with integrated Gene Ontology, Medical Subject Headings and OMIM Morbid Map-based annotations. We applied Fisher's exact test and relative risk to evaluate the statistical significance of the correlations. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of gene-expression profiles integrated with gene-pathway-disease interactions enriched by biomedical ontologies.

Cluster Analysis↗
PubMed1995

Coordinating shared care using electronic data interchange.

Shared care is the situation in which physicians jointly treat the same patient. Shared care may occur with elderly patients suffering from several health problems, patients with chronic disorders such as diabetes, mellitus, obstructive pulmonary diseases, or cardiological disorders. For a number of health problems, including diabetes, shared care protocols have been developed involving division of tasks between health care providers from different disciplines [1]. Optimal communication is considered to be a vital aspect of shared care, both from medical and cost-effectiveness points of view, but at the same time communication forms the bottleneck as physicians often lack time to comply with the protocol [2]. At present, new technologies are emerging that hold the promise of improving communication between health care providers. One such technology is Electronic Data Interchange (EDI), defined as "the replacement of paper documents by standard electronic messages conveyed from one computer to another without manual intervention" [3]. In Europe, the ISO syntax standard EDIFACT has been adopted as the standard for defining EDI-messages [4]. In The Netherlands, coordination of the standardization of health care messages is performed by a national organization. At present, several standardized messages are available for a variety of purposes. One is a message for data exchange between physicians; in this message, however, only physician-patient- and hospital-identifying data are structured, and all medical data is transferred as free text. Consequently, using this message, the receiving system is unable to integrate the data into the computer-based patient record. In order to support shared care, a message is needed that can also transfer the structure of the data in a computer-based record in order to allow integration of records from multiple sources. Therefore, we developed a new message, called MEDEUR, that is designed for integrated patient data exchange between computer-based patient records. The message can contain both administrative and medical data and can be used for transmission of a complete medical record, or sections of it. Our departments are working on a project in which general practitioners and specialists use their own electronic medical record system for storing data of jointly treated patients. In addition, the participating physicians use the MEDEUR message standard in communicating about these patients. The use of EDI enables physicians to transmit patient data electronically to another physician's computer system. The receiving physician can store the data automatically in his electronic medical record without having to re-type the data. We will demonstrate the electronic data interchange functionality of the general practitioner's information system, ELIAS, and the integrated composing and storing of electronic messages. We will also discuss several system design issues.

Computer Communication Networks↗
PubMed2026

mmContext: an open framework for multimodal contrastive learning of omics and text data.

SUMMARY: Multimodal approaches are increasingly leveraged for integrating omics data with textual biological knowledge. Yet there is still no accessible, standardized framework that enables systematic comparison of omics representations with different text encoders within a unified workflow. We present mmContext, a lightweight and extensible multimodal embedding framework built on top of the open-source Sentence Transformers library. The software allows researchers to train or apply models that jointly embed omics and text data using any numeric representation stored in an AnnData.obsm layer and any text encoder available in Hugging Face. mmContext supports integration of diverse biological text sources and provides pipelines for training, evaluation, and data preparation. We train and evaluate models for a RNA-Seq and text integration task, and demonstrate their utility through zero-shot classification of cell types and diseases across four independent datasets. By releasing all models, datasets, and tutorials openly, mmContext enables reproducible and accessible multimodal learning for omics-text integration. AVAILABILITY AND IMPLEMENTATION: Pretrained checkpoints and full source code for our custom MMContextEncoder are available on Hugging Face huggingface.co/jo-mengr. The Python package github.com/mengerj/mmcontext provides the model implementation and training and evaluation scripts for custom training. The releases for the publication can be accessed via zenodo: adata_hf_datasets: doi.org/10.5281/zenodo.19185217 and mmContext: doi.org/10.5281/zenodo.19185493.

Computational Biology↗
PubMed2004

Integrated analysis of genetic, genomic and proteomic data.

The rapid expansion of methods for measuring biological data ranging from DNA sequence variations to mRNA expression and protein abundance presents the opportunity to utilize multiple types of information jointly in the study of human health and disease. Organisms are complex systems that integrate inputs at myriad levels to arrive at an observable phenotype. Therefore, it is essential that questions concerning the etiology of phenotypes as complex as common human diseases take the systemic nature of biology into account, and integrate the information provided by each data type in a manner analogous to the operation of the body itself. While limited in scope, the initial forays into the joint analysis of multiple data types have yielded interesting results that would not have been reached had only one type of data been considered. These early successes, along with the aforementioned theoretical appeal of data integration, provide impetus for the development of methods for the parallel, high-throughput analysis of multiple data types. The idea that the integrated analysis of multiple data types will improve the identification of biomarkers of clinical endpoints, such as disease susceptibility, is presented as a working hypothesis.

Animals↗
PubMed1996

Using PC-based decision-support technology to improve efficiency.

Healthcare organizations do not need advanced information technology systems to take advantage of the information they gather regarding clinical and operational efficiency. PC-based decision support technology is available to analyze an integrated delivery system's (IDS) existing data and integrate it with competitive healthcare industry data from public and proprietary sources. Many system executives have purchased such technology for their IDSs, but few use the data they generated properly or successfully.

Decision Support Systems, Management↗
PubMed2001

GBuilder--an application for the visualization and integration of EST cluster data.

This paper presents a network-centric DNA sequence visualization and analysis tool called GBuilder. The tool is an easy-to-use Java application that can be used to analyze DNA sequence clusters and assemblies. The emphasis is on the analysis of EST data, where these highly redundant collections of low-quality and often alternatively spliced or chimeric sequence data are difficult to explore. The tool has the capacity to visualize similarities or dissimilarities between sequences at the level of the nucleotide base or annotation in many ways. Sequences may also be edited manually. The novel feature of GBuilder is its ability to access different data sources and analysis applications available on the Internet and to integrate these results and functionality back into itself. External resources such as EST cluster databases and conventional command-line analysis applications are integrated and accessed using CORBA (Common Object Request Broker Architecture), which provides a standard implementation independent protocol for integration. New CORBA services can be integrated immediately if they use a known interface described using the Interface Definition Language.

Algorithms↗
PubMedDate not supplied

DREAM: integrated image and traditional data management.

Main objectives and characteristics of computerized radiological image handling in a radiology department, homogeneously integrated with other information typologies, are discussed. The extension of the present DREAM system to image handling functionalities is in progress. The activities are based on the collaboration between the "Università Cattolica del Sacro Cuore (UCSC), Istituto di Radiologia". Hopital Cantonal Universitaire de Genève-Centre d'Informatique Hospitalier (HCUG) and Gesi aiming at the integration of "Osiris", image handling information system implemented by HCUG with DHE middleware implemented by Gesi and UCSC which represents the functional and information core of the entire information system. The initiative is part of "Synapses" project, partially supported by the European Union DG XIII within the program of information technology applications in health care.

Radiology Information Systems↗
PubMed2005

Statistical Viewer: a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser.

BACKGROUND: To facilitate efficient selection and the prioritization of candidate complex disease susceptibility genes for association analysis, increasingly comprehensive annotation tools are essential to integrate, visualize and analyze vast quantities of disparate data generated by genomic screens, public human genome sequence annotation and ancillary biological databases. We have developed a plug-in package for Ensembl called "Statistical Viewer" that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis. RESULTS: Statistical Viewer is an add-on package to the open-source Ensembl Genome Browser and Annotation System that displays disease study-specific linkage and/or association data as 2 dimensional plots in new panels in the context of Ensembl's Contig View and Cyto View pages. An enhanced upload server facilitates the upload of statistical data, as well as additional feature annotation to be displayed in DAS tracts, in the form of Excel Files. The Statistical View panel, drawn directly under the ideogram, illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs. A module called "Get Map" easily converts the genetic locations of markers to genomic coordinates. The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl's Contig- and Cyto- View pages to choose the region to be displayed in Ensembl's "Overview" and "Detailed View" panels. To resolve Association and Fine mapping data plots, a "Detailed Statistic View" plot corresponding to the "Detailed View" may be displayed underneath. CONCLUSION: Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System (DAS) to display supplemental laboratory information such as differentially expressed disease genes in private data tracks. Statistic View is a novel and powerful visual feature that enhances Ensembl's utility as valuable resource for integrative genomic-based approaches to the identification of candidate disease susceptibility genes. At present there are no other tools that provide for the visualization of 2-dimensional plots of quantitative data scores against genomic coordinates in the context of a primary public genome annotation browser.

Chromosome Mapping↗
PubMed2005

A molecular model for axon guidance based on cross talk between rho GTPases.

To systematically understand the molecular events that underlie biological phenomena, we must develop methods to integrate an enormous amount of genomic and proteomic data. The integration of molecular data should go beyond the construction of biochemical cascades among molecules to include tying the biochemical phenomena to physical events. For the behavior and guidance of growth cones, it remains largely unclear how biochemical events in the cytoplasm are linked to the morphological changes of the growth cone. We take a computational approach to simulate the biochemical signaling cascade involving members of the Rho family of GTPases and examine their potential roles in growth-cone motility and axon guidance. Based on the interactions between Cdc42, Rac, and RhoA, we show that the activation of a Cdc42-specific GEF resulted in switching responses between oscillatory and convergent activities for all three GTPases. We propose that the switching responses of these GTPases are the molecular basis for the decision mechanism that determines the direction of the growth-cone expansion, providing a spatiotemporal integration mechanism that allows the growth cone to detect small gradients of external guidance cues. These results suggest a potential role for the cross talk between Rho GTPases in governing growth-cone movement and axon guidance and underscore the link between chemodynamic reactions and cellular behaviors.

Animals↗
PubMed1996

Good maps are straight.

This paper proposes a simplified approach to the assembly of large physical genome maps. The approach focuses on two key problems: (i) the integration of diverse forms of data from numerous sources, and (ii) the detection and removal of errors and anomalies in the data. The approach simplifies map assembly by dividing it into three phases-overlap, linkage and ordering. In the first phase, all forms of overlap data are integrated into a simple abstract structure, called clusters, where each cluster is a set of mutually-overlapping DNA segments. This phase filters out many questionable overlaps in the mapping data. In the second phase, clusters are linked together into a weighted intersection graph. False links between widely separated regions of the genome show up as crooked, branching structures in the graph. Removing these false links produces graphs that are straight, reflecting the linear structure of chromosomes. From these straight graphs, the third phase constructs a physical map. Graph algorithms and graph visualization play key roles in implementing the approach. At present, the approach is at an early stage of development: it has been tested on real and simulated mapping data, and the results look promising. This paper describes the first two phases of the approach in detail, and reports on our progress to date.

Chromosomes, Human, Pair 7↗