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Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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At least 397 records · Page 22Linked to original sources
PubMed1989

Long-term data storage in a clinical laboratory information system.

The clinical laboratory is pressured on one side by physicians and regulators who want the laboratory to keep more detailed patient records available for longer periods and on the other side by physical space and cost constraints which favor rapidly transferring such records to Medical Records or a warehouse from which retrieval is slow and difficult. Various forms of inactive data storage and archiving in machine-readable form are available to address this dilemma, yet these solutions can create even more difficult problems. Two different approaches were developed within the framework of Relational LABCOM to address both the intermediate and long-term storage of data. In this paper we examine the two methods as solutions to the problems, discuss their limitations, and determine why one is superceding the other in the installation base.

Clinical Laboratory Information Systems↗
PubMed2001

Comparisons of gene colinearity in genomes using GeneOrder2.0.

Comparative genomics is enhanced by data mining the rapidly expanding DNA sequence databases. Because of the immense amount of data, computational tools and methods are needed to augment traditional manual visualizations and manipulations of these data. GeneOrder2.0, a Java-based interactive software programme, organizes genome sequence data into tabular and graphical visualizations of the extent of colinearity of genes between any two chromosome genomes of < or =250 kilobases. Both GenBank and proprietary data can be analyzed with this tool.

Computational Biology↗
PubMed1978

Computer assisted monitoring in intensive medicine.

Intensive Medicine is always associated with the problem of handling the mass and assuring the quality of information on vital signs, fluid and blood balance, laboratory data, physiological calculations, etc., required in patient care. A computer based monitoring system for intensive care was introduced in 1973 at the Academic Hospital in Leuven. The basic software was developed at the Peter Bent Brigham Hospital of the Harvard Medical School and the medical division of the Hewlett Packard Company; the computer used was a H.P. 2100 central processor with 32K of core memory. Initially, the program allowed mainly acquisition, storage and retrieval of bedside monitored and manual data of cardiac and circulatory function. Very soon however, the software was extended and modified by the division of "Medical Informatics" in order to meet new or different requirements. In the present situation our vision on the use of computer-assisted monitoring has changed and our present program has been extended as follows : 1. On-line collection and retrieval of bedside monitored data including heart rate, arterial blood pressure (systolic-diastolic-mean) left atrial pressure, central venous pressure, pulmonary artery pressure, intracranial pressure. Trend analysis of those data, with calculation of mean values, standard variation and corresponding t-tests. 2. Computer assistance in performing time consuming calculations on off-line data such as : -- clearance-values (renal function), -- temperature-correction of blood-gasvalues, -- hour-to-hour fluid balance, including calculation of in-sensible losses, -- blood-balance. 3. Data transmission of laboratory results as soon as available in the central laboratory through a direct link between laboratory and I.T.U. 4. Computer assisted E.C.G. analysis. The three first objectives are realised, on-line E.C.G.-analysis is being developed. The same computer serves the remotely located medical and coronary care units and one bed in the emergency department. An assessment of computer assistance in intensive therapy, on nursing labor and on quality of patient care is made.

Clinical Laboratory Techniques↗
PubMed1995

A rapid access motif database (RAMdb) with a search algorithm for the retrieval patterns in nucleic acids or protein databanks.

We present here a codification structure, entirely interfaced with the main packages for biomolecule database management, associated with a new search algorithm to retrieve quickly a sequence in a database. This system is derived from a method previously proposed for homology search in databanks with a preprocessed codification of an entire database in which all the overlapping subsequences of a specific length in a sequence were converted into a code and stored in a hash-coding file. This new algorithm is designed for an improved use of the codification. It is based on the recognition of the rarest strings which characterize the query sequence and the intersection of sorted lists read in the codification structure. The system is applicable to both nucleic acid and protein sequences and is used to find patterns in databanks or large sets of sequences. A few examples of applications are given. In addition, the comparison of our method with existing ones shows that this new approach speeds up the search for query patterns in large data sets.

Algorithms↗
PubMed1984

[An example of applied data processing in medicine: medical management in a dialysis center].

An application of computers to haemodialysis units is presented. In fact these centers are characterised by an enormous amount of data which should benefit from computerization, and therefore in the haemodialysis unit of the Cantonal Hospital, Fribourg, a program has been developed to handle medical data. This program, as far as we know the only one of its kind in Switzerland, has already been in use for the last 9 months. Swiftly, surely and simply it allows storage and retrieval of all the administrative and medical data of each patient. Facility of data retrieval, graphic data display and automatic data evaluation has been found to improve clinical management of patients. It also considerably facilitates scientific work. Once the adaptation period is over it permits definite time savings. We are convinced that, after the necessary period of introduction, computers can be of considerable help in medical care.

Computers↗
PubMed2004

SPIDER: software for protein identification from sequence tags with de novo sequencing error.

For the identification of novel proteins using MS/MS, de novo sequencing software computes one or several possible amino acid sequences (called sequence tags) for each MS/MS spectrum. Those tags are then used to match, accounting amino acid mutations, the sequences in a protein database. If the de novo sequencing gives correct tags, the homologs of the proteins can be identified by this approach and software such as MS-BLAST is available for the matching. However, de novo sequencing very often gives only partially correct tags. The most common error is that a segment of amino acids is replaced by another segment with approximately the same masses. We developed a new efficient algorithm to match sequence tags with errors to database sequences for the purpose of protein and peptide identification. A software package, SPIDER, was developed and made available on Internet for free public use. This paper describes the algorithms and features of the SPIDER software.

Algorithms↗
PubMedDate not supplied

Automated data entry and retrieval for health-care management.

The development and implementation of a unique system for medical information management are described. An automated, optically scanned data entry system (OpScan) was combined with a generalized, interactive, storage and retrieval system, the Medical Information Management System (MIMS). OpScan-MIMS operates via a time-share system and requires minimal acquisition and maintenance of hardware. The primary advantages of OpScan-MIMS are its efficient and rapid method for data entry, lack of requirement for technical skills, user-generated programs, and cost-effectiveness. OpScan-MIMS has been utilized in a clinic for sexually transmitted diseases for immediate audit of medical records, monitoring of quality-assurance systems, retrieval of data for statistical analysis and clinic management, and as a teaching instrument for medical and paramedical trainees. Further applications to other systems of health-care management are being developed.

Community Health Centers↗
PubMed1975

The large data base file structure dilemma.

This paper first presents a brief tutorial on the principal random file organization methods for handling two major applications--Transaction oriented systems and information storage and retrieval systems. It then addresses a particular large data base dilemma, not satisfactorily resolved by any of these methods, and which is currently under active investigation. Two approaches to a solution are described. One is called the hybrid inverted list; the other is based upon an old technique called super-imposed coding. The former has been implemented and has recently been installed in an operational system. Some statistics related to file characteristics in this application are provided, but operational cost and performance statistics are not yet available.

Computers↗
PubMed1993

Extended temporal gradient for the retrograde and anterograde amnesia produced by ibotenate entorhinal cortex lesions in mice.

Effects of ibotenic entorhinal cortex (EC) lesions on both retrograde and anterograde amnesia in mice were assessed using two-choice discrimination tasks learned at different intervals before surgery in two eight-arm radial mazes. The results indicated that EC-lesioned mice were severely impaired in postoperative retention of discrimination problems learned 3 d or 2 weeks prior to surgery, but showed no deficit on problems learned between 4, and up to 6 weeks before surgery, as compared to sham-operated controls. When trained on a novel two-choice discrimination problem (not acquired preoperatively), experimental subjects demonstrated quite normal rates of acquisition, but were impaired in learning its reversal. Furthermore, they exhibited a faster rate of forgetting (anterograde amnesia) relative to controls over a 2-week retention interval. These results indicate that approximately 4 weeks is required before memory for a two-choice spatial discrimination problem no longer depends on the integrity of the entorhinal cortex, and suggests that, beyond this time, an EC-independent memory storage system is capable of supporting the retrieval of information. The data, together with complementary behavioral results, are discussed in the context of current theories of memory storage.

Amnesia↗
PubMed2001

'The surface management system' (SuMS) database: a surface-based database to aid cortical surface reconstruction, visualization and analysis.

Surface reconstructions of the cerebral cortex are increasingly widely used in the analysis and visualization of cortical structure, function and connectivity. From a neuroinformatics perspective, dealing with surface-related data poses a number of challenges. These include the multiplicity of configurations in which surfaces are routinely viewed (e.g. inflated maps, spheres and flat maps), plus the diversity of experimental data that can be represented on any given surface. To address these challenges, we have developed a surface management system (SuMS) that allows automated storage and retrieval of complex surface-related datasets. SuMS provides a systematic framework for the classification, storage and retrieval of many types of surface-related data and associated volume data. Within this classification framework, it serves as a version-control system capable of handling large numbers of surface and volume datasets. With built-in database management system support, SuMS provides rapid search and retrieval capabilities across all the datasets, while also incorporating multiple security levels to regulate access. SuMS is implemented in Java and can be accessed via a Web interface (WebSuMS) or using downloaded client software. Thus, SuMS is well positioned to act as a multiplatform, multi-user 'surface request broker' for the neuroscience community.

Brain Mapping↗