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Results for “Information Retrieval Systems”

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At least 973 records · Page 54Linked to original sources
PubMed1999

Integration of generic indicators for quality management in hospital information systems.

Hospital information systems may contribute in different ways to quality management activities such as monitoring of quality indicators. Most existing quality management activities in hospitals are adjusted to a special medical field or particular disease. These activities often run simultaneously with other procedures and the documentation of patient care. To determine an interdisciplinary integrated quality management procedure, a pilot study was carried out at the Neurosurgery Department and Neonatology Division of the Medical Center of the University of Heidelberg. Predefined generic indicators that may be integrated in an existing information system and used in hospital routine were the basis of this project. The aim of the study was to support the quality management with periodic reports of these indicators. The pilot study showed that there were barriers along the path to an integrated generic quality management. To meet the requirements of routine monitoring, using predefined generic indicators of hospital care, much integration effort, directed at organizational aspects of information processing and information systems architecture, is still needed.

Germany↗
PubMed2004

F2CS: FSSP to CATH and SCOP prediction server.

UNLABELLED: The F2CS server provides access to the software, F2CS2.00, which implements an automated prediction method of SCOP and CATH classifications of proteins, based on their FSSP Z-scores. AVAILABILITY: Free at http://www.weizmann.ac.il/physics/complex/compphys/f2cs/ SUPPLEMENTARY INFORMATION: The site contains links to additional figures and tables.

Algorithms↗
PubMed2006

XQTav: an XQuery processor for Taverna environment.

UNLABELLED: Taverna workbench is an environment for construction, visualization and execution of bioinformatic workflows that integrate specialized tools available through the internet. It is gaining popularity fast, because of supporting the most important bioinformatic services and its simple, yet robust graphical notation. Here we present XQTav-an extension of Taverna that provides full integration with XQuery (the query language for XML) engine. XQTav allows execution of XQuery scripts in Taverna workflow diagrams. All existing Taverna processors can be accessed in the XQuery scripts. This provides an alternative way of specifying subworkflows in Taverna and is useful when one deals with query-like algorithms (e.g. filters and inner joins). Moreover, XQtav may be used to automatically generate an XQuery script that is equivalent to Taverna's workflow. This constitutes another way of creating and enacting bioinformatic workflows: overall structure of a diagram is drawn in Taverna environment, XQuery code is generated and possibly adjusted by hand. It can be executed by XQuery engines or incorporated into other software environments. AVAILABILITY: XQtav is an open source software. It may be downloaded from http://xqtav.sourceforge.net/. The page also contains various tutorials and examples, including the one described in this report.

Algorithms↗
PubMedDate not supplied

Visual analytics.

Explore the source record for details and available documents.

Computer Graphics↗
PubMedDate not supplied

Care planning as a strategy to manage variation in practice: from care plan to integrated person-based record.

This article begins with a summary of the trend toward a person-based health record, and the need to integrate data from a variety of sources to achieve this. A project is described that demonstrated problems with the structure of nursing care plans. These problems affected the ability to integrate care plan data into a clinical database capable of analysis to link control of process with clinical outcome. A second project is described that focused on the development of data sets holding higher-level descriptions suitable for the maintenance of a person-based record, but at a summarized level and with no clinical detail. Finally, a prototype care planning system is described that, while maintaining the data required by the Nursing Process, was more flexibly structured to support analysis and hierarchical levels of description.

Community Health Nursing↗
PubMedDate not supplied

Informatics in radiology (infoRAD): Vendor-neutral case input into a server-based digital teaching file system.

Although digital teaching files are important to radiology education, there are no current satisfactory solutions for export of Digital Imaging and Communications in Medicine (DICOM) images from picture archiving and communication systems (PACS) in desktop publishing format. A vendor-neutral digital teaching file, the Radiology Interesting Case Server (RadICS), offers an efficient tool for harvesting interesting cases from PACS without requiring modifications of the PACS configurations. Radiologists push imaging studies from PACS to RadICS via the standard DICOM Send process, and the RadICS server automatically converts the DICOM images into the Joint Photographic Experts Group format, a common desktop publishing format. They can then select key images and create an interesting case series at the PACS workstation. RadICS was tested successfully against multiple unmodified commercial PACS. Using RadICS, radiologists are able to harvest and author interesting cases at the point of clinical interpretation with minimal disruption in clinical work flow.

Computer-Assisted Instruction↗
PubMed1999

Increasing the diversity of medical data mining through distributed object technology.

Data mining has been recently experiencing a boom of interest from researchers and software producers. In medicine, however, its applications are still rather rare. In this paper, we argue that this is primarily due to the requirements of reproducibility of results and diversity of available data mining tools, both of which are crucially important for medical research. We propose to tackle the diversity requirement by means of distributed object technologies. The results presented here rely on our experience with medical data mining using the method GUHA and with further developing that method.

Artificial Intelligence↗
PubMed2002

Abstracting data warehousing issues in scientific research.

This paper presents the design and implementation of the Idaho Biomedical Data Management System (IBDMS). This system preprocesses biomedical data from the IMPROVE (Improving Control of Patient Status in Critical Care) library via an Open Database Connectivity (ODBC) connection. The ODBC connection allows for local and remote simulations to access filtered, joined, and sorted data using the Structured Query Language (SQL). The tool is capable of providing an overview of available data in addition to user defined data subset for verification of models of the human respiratory system.

Abstracting and Indexing↗
PubMed2002

SmartQuery: context-sensitive links to medical knowledge sources from the electronic patient record.

Physicians have many unmet information needs that arise in the course of patient care. Many clinical questions could potentially be answered by streamlined access to medical literature, textbooks, and clinical guidelines in the context of the electronic medical record. We designed and implemented SmartQuery, a prototype application to provide context-sensitive links from an electronic patient record to relevant medical knowledge sources, then performed a preliminary user evaluation. Our results suggest that such an application may be clinically useful, and provide some insight into problems and priorities for future development.

Expert Systems↗
PubMed2005

The establishment of the photo management system for orthodontics and its clinical application.

It is necessary for orthodontists to collect and analyze the patients' photographic data. By conventional methods, these photo data were commonly saved on film, which were frail and often resulted in data loss. Furthermore, it is not convenient for the orthodontists to consult and study these data during clinical research. A critical problem thus arises in managing these photo data scientifically. The computer technique and picture processing method were employed in the present study to establish the Photo Management System for Orthodontics (PMSO), which makes the administration of patients' photo data more scientific, convenient, and effective than before. This system is characterized as follows: (1) Clinical orthodontists designed and programmed the system, which is "close to clinical reality and serves the clinic". Orthodontists can easily use it without any training course. (2) The images can be imported from many devices, such as digital cameras, scanners, and electronic data storage media such as floppy disks. (3) Even two groups of photos (four images) could be displayed in the same window for comparison and study. This function allows orthodontists to easily observe the differences in the same patient's photos at different stages, which is important to obtain comprehensive knowledge of the patient. (4) The network technique makes it possible for the photos to be shared. The orthodontists can get the patients' photos through the network without going to the radiology department or the imaging room. (5) It is helpful for orthodontic research since the photos can be exported easily in different ways. (6) This is shared software; orthodontists can use it for free.

Computer Communication Networks↗
PubMed2005

Using NLP to extract concepts from chief complaints.

The NLM's MMTx natural language processing (NLP) engine was used to extract concepts from chief complaints entered into an ambulatory electronic medical record (EMR). Of the over 600,000 strings submitted to the process, approximately 25% were assigned at least one concept, with a rate of 2% for incorrect assignments.

Abstracting and Indexing↗
PubMed1995

Verification & validation algorithms for data used in critical care decision support systems.

A decision support system is only as good as the data generating that decision support system. If the data is incorrect, doesn't relate to the other pieces of data, is missing or is not consistent, the decision support system conclusions may be incorrect and inconsistent. While collecting data from several sites during a multicenter randomized clinical trial, we found that some critical data elements were missing, out of correct ranges, totally illogical, and/or inconsistently recorded. In order to get consistent, correct, and dependable information from a our decision support system, the data elements used in that system had to be checked for completeness, valid values, consistent units of measurement, and relationships to other items. Development of data quality assurance rules and the application of those rules is imperative to using the data to generate daily scores for multiple organ failure, sepsis, and barotrauma.

Algorithms↗