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At least 289 records · Page 16Linked to original sources

DiasNet--an Internet tool for communication and education in diabetes.

Although studies have shown that intensive diabetes treatment with the goal of maintaining blood glucose concentrations close to the normal range lead to a substantial reduction of the rate of the complications (e.g. blindness, kidney failure, amputations and circulatory diseases), this can be difficult to achieve using conventional means. It is recognised that a number of patients may have poor control despite specialist care, and this along with devolution of care to non-specialists suggests that alternative interventions should be developed. DiasNet, which is used by patients as a tool for education and communication, is based on a well documented decision support system used by clinicians to give advise on insulin dose. In DiasNet the patients can experiment with their own data, adjusting insulin doses or meals sizes, and thereby learning how to cope with various situations. The system can run both as an ordinary application on a standard PC, and as an Internet application using a standard web browser. The latter enables a new way of communication between patient and clinician. DiasNet is currently being tested on a small group of diabetes patients.

Blood Glucose↗

[Diagnostic imaging and patient database managing systems: The integration of digital information in the experience of an intensive care center].

AIM: To present our experience with integrating digital information on Intensive Care Unit patients (clinical data, laboratory findings, imaging, etc) to create electronic patient records. MATERIAL AND METHODS: Using the hospital Intranet, a connection was established between the Local area Network (LAN) of the Intensive Care Unit (ICU) and the Digital Imaging and Communications in Medicine (DICOM(R)) network of the Radiology Department allowing to receive, process and archive digital images locally at the ICU. Using the software RADclient-RADimage, the information received was managed by an electronic patient record system (DIGISTAT by UMS-Unterberger Medical Software, Florence). All the above software runs on Microsoft WindowsNT 4.0 platforms. RESULTS: Images of various kinds and formats (CT, MRI, etc.) pertaining to the ICU patients were semi-automatically handled and filed on a local server acting as a central databank. The images were then included in the electronic patient record and made available to the end user who could view them using either web technologies (hypertexts were automatically generated that could be viewed through the widely available World Wide Web browsers) or specific viewing utilities supplied with DIGISTAT . DISCUSSION AND CONCLUSIONS: For the intensivist, the handling and filing of data on hospitalised or discharged patients for treatment or research purposes involves having to process large amounts of information. Furthermore, in the event of patients being re-admitted to the unit, it is crucial to have ready access to all the information regarding previous hospital stays, including diagnostic images, to avoid the need for time-consuming searches through the hospital s paper-based archives. The possibility to access clinical information and diagnostic images using a single computer programme proved to be useful both for evaluating the patient s conditions immediately after the imaging procedure and for monitoring the patient s progress over time by comparing the different diagnostic images and imaging procedures. This pilot experience could be seen to provide the basic know-how for applying the method in the future Emergency Department of the A. Gemelli Hospital in Rome.

Computer Communication Networks↗

Redasoft Plasmid 1.1: software for easy, efficient cloning and map drawing.

A computer program is described which creates circular and linear genetic maps with or without sequences, performs restriction analysis, and simulates basic molecular cloning operations. Redasoft Plasmid 1.1 is a user-friendly program for Windows 95/98/NT/2000, designed to generate high quality genetic maps for presentation and publication and to aid the molecular biologist in selecting restriction endonucleases for common molecular cloning experiments. The program incorporates an integrated web browser and can automatically generate complete, labeled maps from sequences on the Internet.

Chromosome Mapping↗

Medical decision support via the internet: PROforma and Solo.

This paper describes the development and application of an integrated technology to support the authoring of intelligent medical knowledge services, such as decision and guideline support, and disseminate them over the Internet. Decision support and guideline enactment are provided by the PROforma technology which is described in detail elsewhere. Solo is a communications infrastructure that supports the delivery of PROforma services over the Internet using a web browser. The PROforma-Solo technology brings together techniques from knowledge engineering and artificial intelligence with software engineering and the Internet to flexibly support decision making and patient management at the point of care. A variety of clinical applications have been implemented and are briefly described.

Artificial Intelligence↗

Application of an intelligent graphical interface to electronic patient records.

Physicians are under a lot of pressure to perform. The power of the computer can be used to reduce the cognitive stresses. The use of an intelligent graphical interface can tailor the information that is presented to the physician. The user can be assured that all the information is presented and that important facts are brought to the users attention. The screen displays can be made to be self organizing. This saves the user the effort of moving and resizing windows. The technology to do this has been developed and has been applied to a web browser interface. This paper describes the advantages of applying this technology to medical records databases.

Artificial Intelligence↗

Mimos: a description framework for exchanging medical image processing results.

Image processing plays increasingly important role in using medical images, both for routine as for research purposes, due to the growing interest in functional studies (PET, MR, etc.). Unfortunately, there exist nearly as many formats for data and results coding as image processing procedures. If Dicom presently supports a kind of structured reporting of image studies, it does not take into account the semantics of the image handling domain. This can impede the exchange and the interpretation of processing results. In order to facilitate the use of image processing results, we have designed a framework for representing image processing results. This framework, whose principle is called an "ontology" in the literature, extends the formalism, which we have used in our previous work on image databases. It permits a systematic representation of the entities and information involved in the processing, that is not only input data, command parameters, output data, but also software and hardware descriptions, and relationships between these different parameters. Consequently, this framework allows the building of standardized documents, which can be exchanged amongst various users. As the framework is based on a formal grammar, documents can be encoded using XML. They are thus compatible with Internet / Intranet technology. In this paper, the main characteristics of the framework are presented and illustrated. We also discuss implementation issues in order to be able to integrate documents, and correlated images, handling these with a classical Web browser.

Image Processing, Computer-Assisted↗

An experimental health smart home and its distributed internet-based information and communication system: first steps of a research project.

We present a study and whole experimental tele-monitoring and medical tele-surveillance system for maintaining patients at home. The project features networked sensors, in a fully equipped apartment, operated by an advanced information and communication system based on Internet, Java, and object oriented modeling. The sensors are connected, mainly wirelessly, with a in-home software module devoted to signals analysis and detection of critical situation such as falls, sickness, sudden palsy, stroke, hypothermia, etc. This module communicates, either via modem or ethernet network, with a remote medical control station in charge of appropriate response to received information and alarms. The system is designed to be a powerful information and communication tools for medical and social workers. It offers a series of functions such as medical file management, user profiles and rights management, drafting and management of ordinances and visit notes, confidentiality of medical information, and management of scenarios of detectable events. The access to the system is allowed to authorized users only (physicians, emergentists, social workers, etc.), and is available on as much authorized computers as needed, by means of a Java applet invoked from any traditional web browsers.

Computer Communication Networks↗

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database.

RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.

Amino Acid Sequence↗

The Virtual Cell project.

The Virtual Cell is a modular computational framework that permits construction of models, application of numerical solvers to perform simulations, and analysis of simulation results. A key feature of the Virtual Cell is that it permits the incorporation of realistic experimental geometries within full 3D spatial models. An intuitive JAVA interface allows access via a web browser and includes options for database access, geometry definition (including directly from microscope images), specification of compartment topology, species definition and assignment, chemical reaction input and computational mesh. The system is designed for cell biologists to aid both the interpretation and the planning of experiments. It also contains sophisticated modelling tools that are appropriate for the needs of mathematical biologists. Thus, communication between these traditionally separate scientific communities can be facilitated. This paper will describe the status of the project and will survey several applications to cell biological problems.

Animals↗

The semantic metadatabase (SEMEDA): ontology based integration of federated molecular biological data sources.

A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg.de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration.

Databases, Genetic↗

[Development of MOIMS on environmental data distribution].

'Environmental WebGIS system for Ganjiang Watershed', based on 1:250,000 topographic spatial database and environmental database of Jiangxi province, was developed. In the system, a hybrid strategy was adopted. And the GIS analysis functions of MapObjects and Map server functions of MOIMS were integrated in the system. Users can use GIS functions, such as zooming in, zooming out, panning, making theme maps, finding geographic objects by environmental attribute values etc., through web browser on the client computers. With the application of the WebGIS system, expanding the GIS users' range, making the GIS operation easily, and assistanting environmental management and decision can be completed.

Environmental Health↗

The Acute Decompensated Heart Failure National Registry (ADHERE): opportunities to improve care of patients hospitalized with acute decompensated heart failure.

Heart failure is a leading cause of hospitalization for adults in the United States. Patients hospitalized with acute decompensated heart failure (ADHF) face a substantial risk of in-hospital mortality and rehospitalization. Despite the large number of patients hospitalized and this substantial risk, data on these patients have been limited and there has been little effort to improve the quality of care for patients hospitalized with ADHF. The Acute Decompensated HEart Failure National REgistry (ADHERE(tm)) was designed to bridge this gap in knowledge and care by prospectively studying characteristics, management, and outcomes in a broad sample of patients hospitalized with ADHF. Participating community and university hospitals identified patients with a primary or secondary discharge diagnosis of heart failure and collected medical history, management, treatments, and health outcomes via secure web browser technology. As of July 2003, 65,180 patients have been enrolled from 263 hospitals. Initial data have provided important insights into the clinical characteristics, patterns of care, and outcomes of these patients. ADHERE documents significant delays in diagnosis and initiation of ADHF therapies as well as substantial under-use of evidence-based, guideline-recommended chronic heart failure therapies at hospital discharge. As such, there are substantial opportunities to improve the quality of care for ADHF patients in the nation's hospitals. The ADHERE Hospital Toolkit has been designed to provide hospital teams with effective proactive instruments to improve the quality of care for patients with ADHF. If successfully implemented, the improvements in short- and long-term clinical outcomes for ADHF patients are expected to be substantial.

Heart Failure↗

Effect of XML markup on retrieval of clinical documents.

OBJECTIVE: To determine the effect on clinical information retrieval of structuring typical clinical documents in XML, according to the general guidelines of Health Level Seven's Clinical Document Architecture. METHODS: One thousand clinical documents of eight frequently occurring types were deidentified and marked up in XML for access using a Web browser. Fifty information-seeking tasks were posed to subjects. The tasks were comprised of two typical clinical question types-individual patient results reporting and cohort identification. A control group of physician subjects could perform only free-text, keyword searching. The treatment group's interface permitted field-based searching of particular sections within each document. Differences in precision and other measures of search success across and between question types were investigated for statistical significance. RESULTS: No statistically significant differences were found between the control and treatment conditions in mean time elapsed or the mean number of records in the final result set. In fact, tasks performed in the treatment condition required a mean number of more steps in the search sequence to a degree that was statistically significant. Tasks performed in the treatment condition had a statistically significant lower rate of mean precision. There was no statistically significant difference between the means of relevance of the individual patient and cohort identification tasks. CONCLUSION: These findings are in line with Tange et al. who found that coarser granularity of clinical narrative gave better results. The results of this experiment also have implications for automatic text processing. Complex tag sets cannot ultimately resolve problems of unstandardized structure; the lack of existing structure within clinical documents is itself a significant limitation.

Humans↗

Efficient web-based navigation of the Foundational Model of Anatomy.

The University of Washington's Foundational Model of Anatomy (FMA)1 is a complex, frame-based model composed of over 170,000 frames collectively specified by more than 1.4 million slot values. The Foundational Model Explorer (FME) was designed to provide simple and intuitive web access to this complex knowledge base. The Foundational Model Explorer (FME) (Figure 1) is built upon the Protégé 2000 knowledge base access library [http://protege.stanford.edu/]. The FME application, associated libraries, and the FMA database all reside on remote servers. Users of the FME are not required to download, install, or set-up any of these components. The FME application, in response to a query, retrieves the appropriate information from the FMA, formats these data into html documents, and transmits them, via the Internet, back to the client where they can be viewed from any standard web browser

Anatomy↗

Real-time soft tissue modelling for web-based surgical simulation: SurfaceChainMail.

The Web provides a useful environment for simple surgical training simulations. A combination of VRML for 3D rendering, and Java code for the simulation engine, has been used for a range of simple neurosurgical demonstrators. However the elements in these simulators are rigid, to avoid the computational complexity of deformable modelling. In this paper we describe a variation of the ChainMail technique that allows us to provide real-time deformable modelling, even in a Web browser environment on a PC. Our new algorithm, SurfaceChainMail, has been used to develop a simulator for the cutting of two layers of tissue, and separating the layers by pulling them apart.

Algorithms↗

Novel retinal genes discovered by mining the mouse embryonic RetinalExpress database.

PURPOSE: Bioinformatics has emerged as a powerful tool for identifying novel genes and pathways associated with retinal biology and disease. The developing mouse retina expresses an exceedingly large and complex variety of genes. Many of these genes have not been characterized but nevertheless are likely to have important developmental or physiological functions. The purpose of this study was to use an in silico approach with a mouse embryonic retinal database of cDNAs/expressed sequence tags (ESTs) named RetinalExpress to identify previously uncharacterized genes that are represented in the developing retina. METHODS: cDNA clones unique to the RetinalExpress database were identified by comparing clones in the RetinalExpress database with those in other cDNA/EST databases. We used a hierarchical filtering procedure with high stringency criteria that included sequence quality, colinearity with hypothetical gene sequences, and absence of any substantial existing annotation to select clones that were likely to represent novel genes. Selected clones were located on mouse chromosomes using National Center for Biotechnology Informatics Map Viewer software and the database from the University of California at Santa Cruz Genome Bioinformatics Web browser. The expression of selected retinal transcripts was determined using reverse transcriptase (RT)-PCR. In situ hybridization of sectioned embryonic and postnatal retinas was performed to determine spatial expression patterns of selected transcripts. RESULTS: Of the 27,765 cDNA clones from RetinalExpress that we filtered through several public cDNA/EST databases, 26 cDNA/EST sequences were identified that, at the time of the analysis, were unique to RetinalExpress. Seventeen clones were selected for RT-PCR analysis, and retinal transcripts corresponding to previously uncharacterized genes were unambiguously detected for six clones. Three genes encoded open reading frames containing putative functional domains; one sequence contained an HMG DNA binding domain, another, an RFX DNA binding domain, and another, a phospholipase C catalytic domain X. Transcripts from the genes encoding DNA binding domains were expressed in embryonic and postnatal retinas with distinct spatial patterns. CONCLUSIONS: The characterization of 26 mouse genes whose partial nucleotide sequences were uniquely represented in the RetinalExpress cDNA/EST database demonstrated the feasibility of retinal gene discovery using in silico analysis. Two of these genes had distinctive spatial expression patterns in the retina and one was likely to function as a DNA binding protein in embryonic and postnatal retinas. The gene identification approach described here demonstrates the usefulness of establishing large cDNA/EST databases from highly specialized neuronal tissues such as the retina to find novel genes.

Animals↗

UUMA. Regional eHealth services in the hospital district of Helsinki and Uusimaa (HUS).

The UUMA approach is based on a stepwise implementation of integrated regional healthcare services to create a virtually borderless healthcare organisation--a patient centred virtual workspace. In the virtual workspace multi-professional teams and patients collaborate and share information regardless of time and place. Presently the regional ehealth network is comprised of four different integrated services between primary, secondary and tertiary care within the county of Uusimaa. The strategic healthcare modules consist of an (1) ereferral and econsultation network, (2) a knowledge-based disease management platform, (3) PACS system and (4) a universal model for integrated regional services between professionals and patients by a link directory service. The ereferral between primary and secondary care not only speeds up the transfer, but also offers an option for communication in the form of econsultation between general practitioners and hospital specialists. By sharing information and knowledge remote econsultations create a new working environment for integrated delivery of eServices between the health care providers. Last year over 60,000 eReferrals were transferred between health care providers. When associated with viewing of patient data through the link directory, interactive econsultations enable supervised care leading to the reduction of outpatient visits and more timely appointments. The link directory service extends the dimensions of networking between organizations by combining legacy systems within regional primary and secondary care. The link directory is an interface to diverse patient information systems, like HUSpacs, containing links pointing to the actual patient data located in remote information systems. The original data including images can be viewed with a web browser, but data can be accessed only with the patient's informed consent. The chronic disease management system is disease specific: information is utilised in parallel to viewing other relevant medical data through the link directory. We aim to create a new working environment for professionals by incorporation of innovative information and communication technology, new organisation of work and re-engineering of workflows. The citizen has an active role in deciding on the use of his medical information, participating in decisions on his care, carrying out guided self-care and taking steps of pro-active prevention.

Computer Communication Networks↗

Gene ontology application to genomic functional annotation, statistical analysis and knowledge mining.

While a massive amount of biomolecular information is increasingly accumulating in different databanks, on the other hand high-throughput technologies are generating a great quantity of data that need to be annotated with the genomic information available, and interpreted. To this aim, the use of specific ontologies can greatly help either in integrating different information stored within heterogeneous databanks, or in identifying and clustering sequence data sharing common characteristics. In the molecular biology domain, the Gene Ontology (GO) is the most developed and widely used ontology. To demonstrate its great utility in the annotation and biological interpretation of gene sets obtained by means of high-throughput experiments, we implemented the web application here described. It enables functional annotations of a given gene set on a genomic scale and across different species. Within our application the annotations provided by the GO vocabulary allow either to easily bind several information from different resources, or to cluster annotated genes according to their biological characteristics. Through the GO structure it is also possible to represent biological concepts with different specificity levels, from very general to very precise concepts. Furthermore, the statistical evaluation of the categorizations provided by the GO annotations enables to highlight the most significant biological characteristics of a gene set, and therefore to mine knowledge from data. Our created tool meets the need to manage a vast quantity of biological data with a simple user interface adapt also for users with limited informatics knowledge, leading them to evaluate the functional significance of experiment's results with graphical views and statistical indexes in a well-known web browser user interface.

Genomics↗