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At least 1,783 records · Page 99Linked to original sources
PubMed2006

Cruella: developing a scalable tissue microarray data management system.

CONTEXT: Compared with DNA microarray technology, relatively little information is available concerning the special requirements, design influences, and implementation strategies of data systems for tissue microarray technology. These issues include the requirement to accommodate new and different data elements for each new project as well as the need to interact with pre-existing models for clinical, biological, and specimen-related data. OBJECTIVE: To design and implement a flexible, scalable tissue microarray data storage and management system that could accommodate information regarding different disease types and different clinical investigators, and different clinical investigation questions, all of which could potentially contribute unforeseen data types that require dynamic integration with existing data. DESIGN: The unpredictability of the data elements combined with the novelty of automated analysis algorithms and controlled vocabulary standards in this area require flexible designs and practical decisions. Our design includes a custom Java-based persistence layer to mediate and facilitate interaction with an object-relational database model and a novel database schema. User interaction is provided through a Java Servlet-based Web interface. RESULTS: Cruella has become an indispensable resource and is used by dozens of researchers every day. The system stores millions of experimental values covering more than 300 biological markers and more than 30 disease types. The experimental data are merged with clinical data that has been aggregated from multiple sources and is available to the researchers for management, analysis, and export. CONCLUSION: Cruella addresses many of the special considerations for managing tissue microarray experimental data and the associated clinical information. A metadata-driven approach provides a practical solution to many of the unique issues inherent in tissue microarray research, and allows relatively straightforward interoperability with and accommodation of new data models.

Database Management Systems↗
PubMed2004

Microarray data mining using gene ontology.

DNA microarray technology allows scientists to study the expression of thousands of genes--potentially entire genomes--simultaneously. However the large number of genes, variety of statistical methods employed and the complexity of biologic systems complicate analysis of microarray results. We have developed a web based environment that simplifies the presentation of microarray results by combining microarray results processed for statistical significance with probe set annotation by Genbank, NCBI RefSeqs, GeneCards and the Gene Ontology. This allows rapid examination and classification of microarray experiments--annotated by NCIBI tools --by Statistical Significance and Gene Oncology Classes. By providing a simple, easily understood interface to large microarray data sets, this tool has been particularly useful for small research groups focused on a small number of related genes and for researchers who want to ask simple questions without the overhead of complex data management and analysis.

Computational Biology↗
PubMed2004

The application of volume-outcome contouring in data warehousing.

Despite a compelling body of published research on the nature of provider volume and clinical outcomes, healthcare executives and policymakers have not managed to develop and implement systems that are useful in directing patients to higher volume providers via selective referral or avoidance. A specialized data warehouse application, utilizing hospital discharge data linked to physician biographical information, allows detailed analysis of physician and hospital volume and the resulting pattern (contour) of related outcomes such as mortality, complications, and medical errors. The approach utilizes a historical repository of hospital discharge data in which the outcomes of interest, important patient characteristics and risk factors used in severity-adjusting of the outcomes are derived from the coding structure of the data.

Diagnosis-Related Groups↗
PubMed2005

Data mining applications in healthcare.

Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. This article explores data mining applications in healthcare. In particular, it discusses data mining and its applications within healthcare in major areas such as the evaluation of treatment effectiveness, management of healthcare, customer relationship management, and the detection of fraud and abuse. It also gives an illustrative example of a healthcare data mining application involving the identification of risk factors associated with the onset of diabetes. Finally, the article highlights the limitations of data mining and discusses some future directions.

Consumer Behavior↗
PubMedDate not supplied

Taking to the road for PI: use the balance scorecard to find your way.

The financial pressures of today's healthcare environment require healthcare professionals to be able to keep all quadrants of quality in check. Tools such as the data card will assist the users of quality data in providing the organization with a catalyst for change. The reproducibility of both the process and the tool has proven to assist an individual organization in creating a clear concise message in the integration of performance measures. This article discusses a methodology and tool for organizations to integrate and evaluate disparate sources of information that can be used to direct priorities for Performance Improvement. The data card is a tool adapted from the Dartmouth Clinical Value Compass used to assist Performance Improvement teams in both the tracking and evaluation of measures related to patient satisfaction, functional status, clinical outcomes, and financial outcomes. The visual enhancement of adding color to the arrows of the compass allows the end users to quickly identify performance improvement opportunities. Examples of the data card are included to assist the readers in identifying specific indicators that can be measured with a specific clinical population as well as adaptation to other uses such as organization-wide indicator measurement Benchmarking is key in defining best practices and has been integrated into the data card.

Arthroplasty, Replacement↗
PubMed2005

A pilot bridging data integration and analytics: BioMediator and R?

Biological research today involves aggregating and analyzing large amounts of data from disparate sources. Tools such as the University of Washington's BioMediator system integrate heterogeneous data. Analytic packages such as the R environment have a rich set of tools to analyze biomedical research data. Our pilot project bridged data integration and analytics in a general way by successfully incorporating the BioMediator system into the R platform for specific analyses on neurophysiologic research data.

Brain↗
PubMed2006

Literature mining for the biologist: from information retrieval to biological discovery.

For the average biologist, hands-on literature mining currently means a keyword search in PubMed. However, methods for extracting biomedical facts from the scientific literature have improved considerably, and the associated tools will probably soon be used in many laboratories to automatically annotate and analyse the growing number of system-wide experimental data sets. Owing to the increasing body of text and the open-access policies of many journals, literature mining is also becoming useful for both hypothesis generation and biological discovery. However, the latter will require the integration of literature and high-throughput data, which should encourage close collaborations between biologists and computational linguists.

Computational Biology↗
PubMed1995

Quantification of color Doppler for the evaluation of tissue vascularization.

Assessment of tissue vascularization with color Doppler (CD) can improve differential diagnosis of tumors. Until now, measurement of flow velocities is restricted to conventional duplex ultrasound of single vessels or semiquantitative scoring of the vessel distribution in CD. We developed a new method for quantification of CD data in organs or tumors by statistical image analysis. Based on standardized image recording, data is acquired from the video output of any ultrasound scanner using a 24-bit color framegrabber in a personal computer. The digitized colors are recognized according to their position in the CD palette bar resulting in an 8-bit color image (number of identified pixels > 99.9%). Within the region of interest, statistics of the detected flow patterns are calculated. The color pixel density and the mean color value varies between recordings of the same image during subsequent systolic peaks with a SD of 10% and 2%, respectively, and within different sections of the same organ or tumor with 25% and 10-50%. This analysis can be used for comparative or longitudinal studies and an objective evaluation of CD in complex vascular formations such as tumors. Its diagnostic impact has already been demonstrated in clinical studies.

Blood Flow Velocity↗
PubMed1996

Transmission of the results of tests for International Olympic Committee-defined drugs of abuse.

The hardware and software facilities for electronic storage, transfer and handling of data is such that multipurpose databases can be made accessible without geographic restriction at low cost. The versatile and flexible underlying structures allow for ease of access and retrieval of data and gives presentation formats fully comparable to printed counterparts. Because of the apparent ease of use and because of the wider distribution of the information, misinterpretation is more likely to occur than in oral or written presentation for more restricted and more culturally homogeneous audiences. This necessitates some degree of harmonisation/standardisation of data on transfer, while allowing local expression forms at sender and receiver ends (Fig. 1). This document is part of an ongoing international effort to agree on some sort of "standardisation" of the transmission and presentation of "laboratory results". It centers on the domain of drugs of abuse as defined by the International Olympic Committee.

Clinical Laboratory Information Systems↗
PubMedDate not supplied

Active index for content-based medical image retrieval.

This paper introduces the active index for content-based medical image retrieval. The dynamic nature of the active index is its most important characteristic. With an active index, we can effectively and efficiently handle smart images that respond to accessing, probing and other actions. The main applications of the active index are to prefetch image and multimedia data, and to facilitate similarity retrieval. The experimental active index system is described.

Abstracting and Indexing↗
PubMedDate not supplied

A low-cost PCI-bus-based ultrasound system for use in image-guided neurosurgery.

A low-cost PCI-bus-based ultrasound sub-system has been developed and integrated into the image-guided neurosurgery system currently in use at the Cleveland Clinic. Two software applications have been developed that integrate real-time ultrasound images with preoperative MR and CT data sets. By tracking the position of the ultrasound probe during surgery, it is possible to display a real time ultrasound image and the corresponding (preoperative) oblique CT or MR slice. This provides immediate positional feedback to the neurosurgeon during the surgical procedure.

Analog-Digital Conversion↗
PubMed2006

International Spinal Cord Injury Core Data Set.

STUDY DESIGN: Survey of expert opinion, feedback, and development of final consensus. OBJECTIVE: Present the background, purpose, development process, and results for the International Spinal Cord Injury (SCI) Core Data Set. SETTING: International. METHODS: A committee of experts was established to select and define data elements to be included in an International SCI Core Data Set. A draft core data set was developed and disseminated to appropriate organisations for comment. All suggested revisions were considered, and a final version of the core data set was disseminated again for approval and adoption. RESULTS: The core data set consists of 24 variables, including basic demographic characteristics, dates of admission and discharge from initial acute and rehabilitation care, cause of injury, place of discharge, presence of vertebral fractures and associated injuries, occurrence of spinal surgery, and measures of neurological and ventilator status. CONCLUSION: Collection of the core data set should be a basic ingredient of all future studies of SCI to facilitate accurate description of patient populations and comparison of results across published studies from around the world.

Database Management Systems↗
PubMed2001

Integration of a picture archiving and communication system with videocapture and computed radiography in a dental hospital.

A method for the integration of a picture archiving and communication system (PACS) at Kyushu University Dental Hospital with radiological information (RIS) and hospital information (HIS) systems is described. CT, US and DSA from different manufacturers were integrated by videocapture and then subsequently integrated with computed radiography (CR) by means of DICOM. The approximate amount of data stored each month on optical discs is 2 GB. The system does not incorporate intra-oral radiography.

Angiography, Digital Subtraction↗
PubMed2005

Statistical dynamic image reconstruction in state-of-the-art high-resolution PET.

Modern high-resolution PET is now more than ever in need of scrutiny into the nature and limitations of the imaging modality itself as well as image reconstruction techniques. In this work, we have reviewed, analysed and addressed the following three considerations within the particular context of state-of-the-art dynamic PET imaging: (i) the typical average numbers of events per line-of-response (LOR) are now (much) less than unity, (ii) due to the physical and biological decay of the activity distribution, one requires robust and efficient reconstruction algorithms applicable to a wide range of statistics and (iii) the computational considerations in dynamic imaging are much enhanced (i.e., more frames to be stored and reconstructed). Within the framework of statistical image reconstruction, we have argued theoretically and shown experimentally that the sinogram non-negativity constraint (when using the delayed-coincidence and/or scatter-subtraction techniques) is especially expected to result in an overestimation bias. Subsequently, two schemes are considered: (a) subtraction techniques in which an image non-negativity constraint has been imposed and (b) implementation of random and scatter estimates inside the reconstruction algorithms, thus enabling direct processing of Poisson-distributed prompts. Both techniques are able to remove the aforementioned bias, while the latter, being better conditioned theoretically, is able to exhibit superior noise characteristics. We have also elaborated upon and verified the applicability of the accelerated list-mode image reconstruction method as a powerful solution for accurate, robust and efficient dynamic reconstructions of high-resolution data (as well as a number of additional benefits in the context of state-of-the-art PET).

Algorithms↗
PubMed2002

UniBLAST: a system to filter, cluster, and display BLAST results and assign unique gene annotation.

MOTIVATION: More and more often, a gene is epitomized by a large number of sequences in GenBank. This high redundancy makes it very difficult to identify a unique best match for a query sequence from its BLAST results. We developed a novel program UniBLAST that filters out uninformative hits, clusters the redundant hits, groups the hits by LocusLink, and graphically displays the results. We also implemented a scoring function in UniBLAST to assign a unique gene name to a query sequence. UniBLAST significantly increases the efficiency of gene annotation. AVAILABILITY: The program is available at http://south.genomics.org.cn/software/uniblast/index.html CONTACT: uniblast@genomics.org.cn; wei@nexusgenomics.com

Cluster Analysis↗
PubMed2002

The Gene Resource Locator: gene locus maps for transcriptome analysis.

Since the advent of the draft human genome sequence there has been growing interest in transcriptome analysis based on genomic data. The Gene Resource Locator (GRL) assembles gene maps that include information on gene-expression patterns, cis-elements in regulatory regions and alternatively spliced transcripts. The database was constructed using customized software, and currently contains 2.2 million alignments (exon-intron structures). The alignments have been annotated and integrated into a system that encompasses approximately 90 000 EST loci sharing common exons, 8091 alternatively spliced transcript groups, 10 801 expression-profile groups, 8066 candidate regulatory regions in full-length cDNAs, and 1 million SNP loci. We have used Flash technology to build a dynamic web viewer that facilitates browsing through the millions of alignments. All of the information is available through the World Wide Web at the Gene Resource Locator web site (http://grl.gi.k.u-tokyo.ac.jp).

Alternative Splicing↗
PubMed2005

Image change detection algorithms: a systematic survey.

Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.

Algorithms↗
PubMed2004

Error analysis of pure rotation-based self-calibration.

Self-calibration using pure rotation is a well-known technique and has been shown to be a reliable means for recovering intrinsic camera parameters. However, in practice, it is virtually impossible to ensure that the camera motion for this type of self-calibration is a pure rotation. In this paper, we present an error analysis of recovered intrinsic camera parameters due to the presence of translation. We derived closed-form error expressions for a single pair of images with nondegenerate motion; for multiple rotations for which there are no closed-form solutions, analysis was done through repeated experiments. Among others, we show that translation-independent solutions do exist under certain practical conditions. Our analysis can be used to help choose the least error-prone approach (if multiple approaches exist) for a given set of conditions.

Algorithms↗