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At least 361 records · Page 20Linked to original sources
PubMed2005

Evaluation of statistical association measures for the automatic signal generation in pharmacovigilance.

Pharmacovigilance aims at detecting the adverse effects of marketed drugs. It is generally based on the spontaneous reporting of events thought to be the adverse effects of drugs. Spontaneous Reporting Systems (SRSs) supply huge databases that pharmacovigilance experts cannot exhaustively exploit without data mining tools. Data mining methods; i.e., statistical association measures in conjunction with signal generation criteria, have been proposed in the literature but there is no consensus regarding their applicability and efficiency, especially since such methods are difficult to evaluate on the basis of actual data. The objective of this paper is to evaluate association measures on simulated datasets obtained with SRS modeling. We compared association measures using the percentage of false positive signals among a given number of the most highly ranked drug-event combinations according to the values of the association measures. By considering 150 drugs and 100 adverse events, these percentages of false positives, among the 500 most highly ranked drug-event couples, vary from 1.1% to 53.4% (averages over 1000 simulated datasets). As the measures led to very different results, we could identify which measures appeared to be the most relevant for pharmacovigilance.

Adverse Drug Reaction Reporting Systems↗
PubMed1994

HELP the next generation: a new client-server architecture.

A new client-server based system which is centered around a lifetime data repository (LDR) is under construction. The goal of the new system is to maintain the patient centered decision support aspects of the existing HELP* system while providing an open architecture that supports faster application development and allows execution of applications to be distributed across many computers. These goals are achieved by implementing the system with software components that are commercially available or by adhering to national and international standards for software integration. Keys to successful integration include the use of MS-DOS @, OS/2#, and UNIX Section as operating systems, Microsoft OLE 2.0 as a standard interface to the clinical database, the use of TUXEDO as a transaction/communication manager, and the use of ORACLE [symbol: see text] RDBMS as the underlying database management system.

Computer Communication Networks↗
PubMed1998

Integrating clinical and laboratory data in genetic studies of complex phenotypes: a network-based data management system.

The identification of genes underlying a complex phenotype can be a massive undertaking, and may require a much larger sample size than thought previously. The integration of such large volumes of clinical and laboratory data has become a major challenge. In this paper we describe a network-based data management system designed to address this challenge. Our system offers several advantages. Since the system uses commercial software, it obviates the acquisition, installation, and debugging of privately-available software, and is fully compatible with Windows and other commercial software. The system uses relational database architecture, which offers exceptional flexibility, facilitates complex data queries, and expedites extensive data quality control. The system is particularly designed to integrate clinical and laboratory data efficiently, producing summary reports, pedigrees, and exported files containing both phenotype and genotype data in a virtually unlimited range of formats. We describe a comprehensive system that manages clinical, DNA, cell line, and genotype data, but since the system is modular, researchers can set up only those elements which they need immediately, expanding later as needed.

Clinical Laboratory Information Systems↗
PubMed1994

A model for the assessment of medical workstations for health care support.

The development of medical workstations for the support of patient care, the assessment of care, management support, and education is just at its beginning. During the Working Conference on the Health care Professional Workstation held in Washington DC, June 1993, several aspects of such workstations were discussed, but it was also recognized that prototyping or learning by experience could be a rich source to further promote the progress in this field. Eight such prototypes or already operational medical workstations were demonstrated and a preliminary user assessment was done to obtain a first insight in the advantages and the type of criteria of such evaluations. It was concluded that such assessments were of great value to (i) give feedback to the designers of medical workstations, (ii) indicate areas of strength and for further research, and (iii) to offer criteria to potential users of such workstations for making decisions on using such systems. The assessment criteria deal with functionality, architecture, user interfaces, communications and integration, and data and knowledge management.

Artificial Intelligence↗
PubMed2003

An extensible application for assembling annotation for genomic data.

SUMMARY: AnnBuilder is an R package for assembling genomic annotation data. The system currently provides parsers to process annotation data from LocusLink, Gene Ontology Consortium, and Human Gene Project and can be extended to new data sources via user defined parsers. AnnBuilder differs from other existing systems in that it provides users with unlimited ability to assemble data from user selected sources. The products of AnnBuilder are files in XML format that can be easily used by different systems. AVAILABILITY: (http://www.bioconductor.org). Open source.

Database Management Systems↗
PubMed2004

The gene ontology categorizer.

The Gene Ontology Categorizer, developed jointly by the Los Alamos National Laboratory and Procter & Gamble Corp., provides a capability for the categorization task in the Gene Ontology (GO): given a list of genes of interest, what are the best nodes of the GO to summarize or categorize that list? The motivating question is from a drug discovery process, where after some gene expression analysis experiment, we wish to understand the overall effect of some cell treatment or condition by identifying 'where' in the GO the differentially expressed genes fall: 'clustered' together in one place? in two places? uniformly spread throughout the GO? 'high', or 'low'? In order to address this need, we view bio-ontologies more as combinatorially structured databases than facilities for logical inference, and draw on the discrete mathematics of finite partially ordered sets (posets) to develop data representation and algorithms appropriate for the GO. In doing so, we have laid the foundations for a general set of methods to address not just the categorization task, but also other tasks (e.g. distances in ontologies and ontology merger and exchange) in both the GO and other bio-ontologies (such as the Enzyme Commission database or the MEdical Subject Headings) cast as hierarchically structured taxonomic knowledge systems.

Database Management Systems↗
PubMed2005

Design of a description language for generating wrapper to collect biological data.

The biological data are scattered in various areas with various formats and they are changing continuously. Therefore, data integration becomes an important issue to provide researcher a dynamic access of data. In the data integration process, the method of extracting heterogeneous data dynamically from the data source is an essential part. Data extraction method using wrapper can provide flexibility and extensibility to an integration system.

Computational Biology↗
PubMed2004

Association rule mining in peer-to-peer systems.

We extend the problem of association rule mining--a key data mining problem--to systems in which the database is partitioned among a very large number of computers that are dispersed over a wide area. Such computing systems include grid computing platforms, federated database systems, and peer-to-peer computing environments. The scale of these systems poses several difficulties, such as the impracticality of global communications and global synchronization, dynamic topology changes of the network, on-the-fly data updates, the need to share resources with other applications, and the frequent failure and recovery of resources. We present an algorithm by which every node in the system can reach the exact solution, as if it were given the combined database. The algorithm is entirely asynchronous, imposes very little communication overhead, transparently tolerates network topology changes and node failures, and quickly adjusts to changes in the data as they occur. Simulation of up to 10,000 nodes show that the algorithm is local: all rules, except for those whose confidence is about equal to the confidence threshold, are discovered using information gathered from a very small vicinity, whose size is independent of the size of the system.

Algorithms↗
PubMed1991

Large database management in clinical dental research.

Previously the management and analysis of large databases for longitudinal clinical dental research has been severely restricted by the costs of custom-made software and access to suitable computing equipment. However, the recent availability of powerful personal computers and the use of the Scientific Information Retrieval Database Management System (SIR/DBMS) in association with BMDP Statistical Software has now created an enormously powerful tool for extensive and fast data manipulation requiring relatively few commands and the capability to easily perform detailed statistical analyses.

Computer Graphics↗
PubMed1999

Seamless multiresolution display of portable wavelet-compressed images.

Image storage, display, and distribution have been difficult problems in radiology for many years. As improvements in technology have changed the nature of the storage and display media, demand for image portability, faster image acquisition, and flexible image distribution is driving the development of responsive systems. Technology, such as the wavelet-based multiresolution seamless image database (MrSID) portable image format (PIF), is enabling image management solutions that address the shifting "point-of-care." The MrSID PIF employs seamless, multiresolution technology, which allows the viewer to determine the size of the image to be viewed, as well as the position of the viewing area within the image dataset. In addition the MrSID PIF allows control of the compression ratio of decompressed images. This capability offers the advantage of very rapid image recall from storage devices and portability for rapid transmission and distribution using the internet or wide-area networks. For example, in teleradiology, the radiologist or other physician desiring to view images at a remote location has full flexibility in being able to choose a quick display of an overview image, a complete display of a full diagnostic quality image, or both without compromising communication bandwidth. The MrSID algorithm will satisfy Joint Photographic Experts Group (JPEG) 2000 standards, thereby being compatible with future versions of the Digital Imaging and Communications in Medicine (DICOM) standard for image data compression.

Algorithms↗
PubMed2002

AngioDB: database of angiogenesis and angiogenesis-related molecules.

Angiogenesis is the formation of new capillaries sprouting from pre-existing vessels. Angiogenesis occurs in a variety of normal physiological and pathological conditions and is regulated by a balance of stimulatory and inhibitory angiogenic factors. The control of this balance may fail and result in the formation of a pathologic capillary network during the development of many diseases. Therefore, we developed the angiogenesis database (AngioDB), which can provide a signaling network of angiogenesis-related biomolecules in human. Each record of AngioDB consisted of 12 fields and was developed by using a relational database management system. For the retrieval of data, Active Server Page (ASP) technology was integrated in this system. Users can access the database by a query or imagemap browsing program. The retrieving system also provides a list of angiogenesis-related molecules classified by three categories, and the database has an external link to NCBI databases. AngioDB is available via the Internet at http://angiodb.snu.ac.kr/.

Amino Acid Sequence↗
PubMed1997

[A query system for the "SINTESI" database in scientific research and medical practice].

"SINTESI release 1.0" is an application for Windows that was designed to enable a practical approach to day-hospital evaluation and management of several metabolic and instrumental parameters. "SINTESI" provides electronic archives such as demographics, history, follow-up, laboratory, electrocardiogram, Doppler echocardiography, vascular echo-Doppler, Holter ECG, nuclear imaging, radiology, ergometric testing, ambulatory blood pressure monitoring, hemodynamics. We have improved the first release (1.0) with a new application that queries the database ("SINTESI release 2.0"). The new query application, developed in collaboration with experts of the Italian Group for the Study of Atherosclerosis and Metabolic Diseases, was designed with the central file displaying buttons that recall electronic archives, allowing to select the variables for the query. At the end of each operation, the user always returns to the central file, where it builds the query formula by "AND/OR" logic operators. Query formula and results can be recorded to be used whenever needed. The results of the query can be exported as DBF or ASCII files for analysis with statistical packages. This feature allows the use of the data bank for medical research.

Cardiovascular Diseases↗
PubMed2001

Data management procedures in the Asthma Clinical Research Network.

Well-designed data management processes are essential in ensuring the quality of data collected in multicenter clinical trials. This paper describes the data management processes and systems that were developed by the data coordinating center of the Asthma Clinical Research Network. A combination of manual and electronic processes has been designed to process clinical trial data from the point of collection to statistical analysis. A distributed database management system consisting of modular applications for separate data processing activities was developed to enter, track, verify, validate, and edit collected data. In addition, processes for monitoring and reporting data quality are discussed.

Asthma↗
PubMedDate not supplied

Mining complex clinical data for patient safety research: a framework for event discovery.

Successfully addressing patient safety requires detecting medical events effectively. Given the volume of patients seen at medical centers, detecting events automatically from data that are already available electronically would greatly facilitate patient safety work. We have created a framework for electronic detection. Key steps include: selecting target events, assessing what information is available electronically, transforming raw data such as narrative notes into a coded format, querying the transformed data, verifying the accuracy of event detection, characterizing the events using systems and cognitive approaches, and using what is learned to improve detection.

Database Management Systems↗
PubMed2005

Evaluation of biomedical text-mining systems: lessons learned from information retrieval.

Biomedical text-mining systems have great promise for improving the efficiency and productivity of biomedical researchers. However, such systems are still not in routine use. One impediment to their development is the lack of systematic and rigorous evaluation, comparable to the approaches developed for information retrieval systems. The developers of text-mining systems need to improve both test collections for system-oriented evaluation and undertake user-oriented evaluations to determine the most effective use of their systems for their intended audience.

Algorithms↗
PubMed2005

ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text.

ABNER (A Biomedical Named Entity Recognizer) is an open source software tool for molecular biology text mining. At its core is a machine learning system using conditional random fields with a variety of orthographic and contextual features. The latest version is 1.5, which has an intuitive graphical interface and includes two modules for tagging entities (e.g. protein and cell line) trained on standard corpora, for which performance is roughly state of the art. It also includes a Java application programming interface allowing users to incorporate ABNER into their own systems and train models on new corpora.

Algorithms↗
PubMed2006

The LCB Data Warehouse.

UNLABELLED: The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that provides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE system), analysis and publication of microarray data. Important features of the system include: access to established methods within R/Bioconductor for data analysis, built-in connection to the Gene Ontology database and a scripting facility for automatic recording and re-play of all the steps of the analysis. The service is up and running on a high performance server. At present there are more than 150 registered users. AVAILABILITY: An open functional version is available at https://dw.lcb.uu.se/index.phtml?i_login=test. User accounts are created upon request. Additional facilities including plug-ins, user documentation and a password protected data storage system are available from http://www.lcb.uu.se/lcbdw.php

Computer Graphics↗