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Results for “Data Storage And Retrieval”

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At least 127 records · Page 7Linked to original sources
PubMed1992

Automated scanning and digitizing of roentgenographs for documentation and research.

A comprehensive system has been developed for analyzing and reporting the results of total hip arthroplasty. The personal-computer-based system links patient demographic data with digital storage, retrieval, and analysis of roentgenographs. The system consists of a roentgenograph scanner for converting sheet film to digital data, an optical mark reader for patient data input, an archiving system with optical storage, and a physician display station for preoperative planning and postoperative evaluation. Once a roentgenograph has been digitized and stored, the image can be retrieved and manipulated in a manner not possible with the original sheet film. A selected roentgenograph can be brought to full or enlarged scale, enhanced, and overlaid with templates for preoperative planning or for postoperative measurement of changes. In addition, an intelligent database system has been developed for linking patient demographic information with the roentgenographic data. The database system employs uniform criteria and terminology and allows the retrospective study and statistical analysis of comparable cases. Three machine-readable code sheets are used: Form A, Replacement of the Hip; Form B, Hip Prosthesis Reoperation; and Form C, Follow-up. Forms A and B contain information concerning anamnesis, diagnosis, treatment, postoperative course, recovery, and discharge of the patient from the hospital. Form C provides information on physical examination, pain, mobility of the hip, walking ability, and evaluation of the results by the surgeon as well as the patient.

Computer Systems↗
PubMedDate not supplied

IRAP--a system for the retrieval and analysis of orthopaedic implant data.

An interactive computer system for the storage, retrieval and analysis of standardized clinical and material characterization data associated with orthopaedic implants is described. The system consists basically of four independent modules. The essence of the system centers on the cross-referencing capabilities which are virtually unlimited. The system has been designed for use by non-computer trained personnel.

Humans↗
PubMed1978

On-line computer storage, retrieval, and reporting of coded angiographic data.

Interpretations of angiographic images have been coded and stored using an on-line computer terminal for seven years. Decoded angiographic information is incorporated in computer-generated reports which are printed on demand after completion of cardiac catheterization procedures. Currently, almost 5,500 cases are stored in an off-line data base which has been designed to help identify patterns with prognostic potential. Also, the program has helped standardize angiographic nomenclature, saved much clerical time, and virtually eliminated clerical errors. The program interacts with other software in the hospital, avoiding repetitious entries. The advantages and shortcomings of the program and commonly used approaches to computer storage/retrieval of radiographic information are described.

Angiography↗
PubMed1986

Microcomputer applications in allied health education: some new alternatives.

Allied health educators should consider that today low-cost microcomputer hardware and software that can significantly enhance the efficiency and effectiveness of teaching are available. These alternative educational applications of microcomputer technology in allied health can be developed by faculty themselves without programming or reliance on computing experts. Such applications include word-processing software for creation and revision of syllabi, exams, and handouts; data base management software for creation of large sets of bibliographic references, storage and retrieval of data on student admissions and matriculation, and management of clinical affiliations; spreadsheet software for preparation of budgets, calculation of student grades and test item analyses, and demonstration of physiologic and biologic phenomena; and graphics software for production of graphs and charts and printing of graphic images. These instructional support uses of microcomputers hold the greatest promise for near-term cost benefit in allied health education.

Audiovisual Aids↗
PubMed1988

MENTHOR, a database system for the storage and retrieval of three-dimensional molecular structures and associated data searchable by substructural, biologic, physical, or geometric properties.

MENTHOR is a database system for the storage and retrieval of three-dimensional coordinate and charge information on molecules as well as of traditional biological and physical properties. Our molecular graphics system retrieves from MENTHOR structural information in individual molecules and receptor map/macromolecular binding site hypotheses. Substructural searches of MENTHOR are used to find starting coordinates for molecular modeling and traditional database searches of MENTHOR identify compounds for which modeling is needed. It also forms the data to be searched with ALLADDIN, our substructure/geometric search program. MENTHOR expedites molecular modeling by organizing previous work and facilitating transmission of information between individuals. Examples from modeling of D-2 receptor agonists are shown.

Drug Design↗
PubMed2001

An evaluation of standard retrieval algorithms and a binary neural approach.

In this paper we evaluate a selection of data retrieval algorithms for storage efficiency, retrieval speed and partial matching capabilities using a large Information Retrieval dataset. We evaluate standard data structures, for example inverted file lists and hash tables, but also a novel binary neural network that incorporates: single-epoch training, superimposed coding and associative matching in a binary matrix data structure. We identify the strengths and weaknesses of the approaches. From our evaluation, the novel neural network approach is superior with respect to training speed and partial match retrieval time. From the results, we make recommendations for the appropriate usage of the novel neural approach.

Algorithms↗
PubMedDate not supplied

Comparison of EPA's QMS to SEI's CMMI.

EPA and other government organizations make decisions based on environmental measurements. How good are the data? How well are the data generators performing? What measurements apply to them? How can the data life cycle processes be improved so data generators can continually provide the best data? EPA's Quality Management System requirements go beyond evaluation of environmental data quality itself to examine systems associated with production, collection, processing (validation/verification), transfer, reduction, storage, and retrieval of data throughout a life cycle. This QMS specifies minimum quality requirements for particular environmental programs. But how can you measure and compare programs that go well beyond the minimum, towards optimal quality? This paper compares EPA's requirements for Quality Management Systems (R2) and Project Plans (R5) to the Software Engineering Institute Capability Maturity Model (CMMISM). The CMMISM model provides for growth (staged or continuous) and a comprehensive assessment that is not yet provided in EPA's R2 or R5. Properly implemented, the CMMISM model serves as a quality framework for integrating and aligning organizational processes and implementing a program of continual process improvements. It identifies process areas ("things to do"), and provides measures of performance ("how well things are done") against specific goals and practices. CMMISM uses a Systems Engineering Management approach, built on process models, that helps identify "how good" the system is. Goodness is defined as stages in a complete model for optimal operation. CMMISM provides two methods for evaluating the goodness of the project. The Staged model in CMMISM provides a Maturity Level that is a well-defined evolutionary plateau describing the manner in which a specified set of processes are performed. As the organization advances in maturity, these levels become more defined and processes are tailored for specific project needs. The other method is called the Continuous Model in CMMISM, and it allows you to achieve Capability Levels. These are used to describe how well each project is doing in relationship to the different process areas. There are six Capability Levels from 0-5 that apply to individual process areas. Organizations using the Capability Level approach can select individual process areas that are important to specific projects and work to improve the processes. Improving capability in individual process areas raises the organization's overall quality of products delivered. The Continuous Model, unlike the Staged Model, lets you pick higher maturity level process areas before completing all of the ones below. Environmental measurement programs need to focus on the quality of the systems where data are collected, processed, transferred, and so forth. DynCorp built on the quality foundation from our experience with R2 to successfully implement CMMISM practices in the development of Forms II Lite and other applications. DynCorp is now migrating to the CMMISM model that has evolved from the existing CMM model. The CMMISM model focuses on the full cycle of Requirements Management from identification, development, collection, refinement, analysis, and validation throughout a project life cycle. It also has a more refined focus on the identification, development, collection, analysis, and evaluation of meaningful measurements, so the results can be used to improve a process or product.

Academies and Institutes↗
PubMed2004

Utility and limitations of genetic disease databases in clinical genetics research: a neurofibromatosis 1 database example.

Databases that collect clinical information on patients with particular genetic diseases can be used to investigate the clinical history of a disorder, its genetics, and genotype-phenotype correlations. A database can also serve as a valuable source of patients for studies of disease pathogenesis, variability, or treatment. We review the strengths and limitations of genetic disease databases in the context of our experience with the National Neurofibromatosis Foundation International Database (NNFFID). Genetic disease databases have been developed by individual investigators, scientific consortia, patient support organizations, and commercial enterprises. Databases vary from simple lists of affected individuals to comprehensive collections of detailed clinical and genetic information. Data may be obtained from people who volunteer to be included, systematic assessments of patients seen at participating medical centers, or population-based registries. Access to information may be highly restricted or widely available. These variables all affect the possible uses and usefulness of the data for research. Technical aspects of data entry, organization, storage, and retrieval, as well as issues related to data quality, confidentiality, and security, help determine how well a system actually functions. We discuss examples of research that have been accomplished with genetic disease databases and make recommendations regarding the organization and operation of these resources.

Biomedical Research↗
PubMed2002

SPINS: standardized protein NMR storage. A data dictionary and object-oriented relational database for archiving protein NMR spectra.

Modern protein NMR spectroscopy laboratories have a rapidly growing need for an easily queried local archival system of raw experimental NMR datasets. SPINS (Standardized ProteIn Nmr Storage) is an object-oriented relational database that provides facilities for high-volume NMR data archival, organization of analyses, and dissemination of results to the public domain by automatic preparation of the header files required for submission of data to the BioMagResBank (BMRB). The current version of SPINS coordinates the process from data collection to BMRB deposition of raw NMR data by standardizing and integrating the storage and retrieval of these data in a local laboratory file system. Additional facilities include a data mining query tool, graphical database administration tools, and a NMRStar v2. 1.1 file generator. SPINS also includes a user-friendly internet-based graphical user interface, which is optionally integrated with Varian VNMR NMR data collection software. This paper provides an overview of the data model underlying the SPINS database system, a description of its implementation in Oracle, and an outline of future plans for the SPINS project.

Archives↗
PubMed2000

Content-based retrieval of dynamic PET functional images.

The recent information explosion has led to massively increased demand for multimedia data storage in integrated database systems. Content-based retrieval is an important alternative and complement to traditional keyword-based searching for multimedia data and can greatly enhance information management. However, current content-based image retrieval techniques have some deficiencies when applied in the biomedical functional imaging domain. In this paper, we presented a prototype design for a content-based functional image retrieval database system for dynamic positron emission tomography. The system supports efficient content-based retrieval based on physiological kinetic features and reduces image storage requirements. This design makes it possible to maintain a large number of patient data sets online and to rapidly retrieve dynamic functional image sequences for interpretation and generation of physiological parametric images, and offers potential advantages in medical image data management and telemedicine, as well as providing possible opportunities in the statistical and comparative analysis of functional image data.

Computer Graphics↗
PubMed1982

Microelectronics and computers in medicine.

Microelectronics and computers are in use in virtually every aspect of modern medicine. Computers are used widely in medical research, where an important need is for better microelectronic sensors for data acquisition. In medical practice, data collection from patients as well as subsequent storage, retrieval, and manipulation of data are enhanced by the computer. In medical decision-making computers improve accuracy, increase cost-efficiency, and advance understanding of the structure of medical knowledge and of the decision-making process itself. Powerful new noninvasive diagnostic instruments including x-ray tomographic scanners and ultrasonic imaging systems are based on computers. The efficiency and scope of clinical laboratory procedures and advanced analytical instruments are greatly increased by computerization, and careful application of computers has improved the interpretation of diagnostic tests, such as the electrocardiogram, and monitoring of critically ill patients. The powerful sensory, computational, memory, and display capabilities of microcomputer systems and their compact size offer new opportunities to relieve functional deficiencies associated with loss of limbs, paralysis, speech impediments, deafness, and blindness.

Clinical Laboratory Techniques↗