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Results for “Information Retrieval Systems”

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PubMed2005

Managing healthcare information: the role of the broker.

We describe a prototype information broker that has been developed to address typical healthcare information needs, using web services to obtain data from autonomous, heterogeneous sources. Some key features are reviewed: how data sources are turned into data services; how we enforce a distributed access control policy; and how semantic interoperability is achieved between the broker and its data services. Finally, we discuss the role that such a broker might have in a Grid context, as well as the limitations this reveals in current Grid provision.

Computer Systems↗
PubMed1994

The AIM SEISMED guidelines for system development and design.

Discussion of the process of drafting guidelines that provide managers within the Health Care Establishments with guidance on how to ensure that safety, security and soundness aspects are taken care of in the development and design of new systems to be used within their establishments. The resulting guidelines focus on requirements for organisations which are involved in the development and design of (secure) information systems to be used in a health care environment, where confidentiality, integrity and availability of the stored data is of the utmost importance. Because of the importance of one European direction in constructing and maintaining secure environments we took the ITSEC criteria as the main guide.

Computer Security↗
PubMed1996

Database and knowledge base integration in decision support systems.

Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases.

Artificial Intelligence↗
PubMed1988

Organizational resources for the occupational therapist in the public schools.

Many organizational resources can assist the public school occupational therapist in fulfilling his or her commitment to the population being served. This paper presents four types of organizational resources that are readily available to the therapist: professional, nonprofit/volunteer, and commercial organizations, and information search and retrieval systems. Each category of resource contains examples and a brief description of each example. Descriptions of professional and nonprofit/volunteer organizations include information about their purpose, membership, and publications. The examples in each of these categories cover a variety of disciplines and disabling conditions; however, all are involved with and provide information about children with disabilities. Descriptions of commercial organizations highlight specific products that are applicable to occupational therapy in the schools. Descriptions of information search and retrieval systems state the kinds of materials each system maintains and provide information on how to gain access to each system.

Humans↗
PubMedDate not supplied

Providing concept-oriented views for clinical data using a knowledge-based system: an evaluation.

OBJECTIVE: Clinical information systems typically present patient data in chronologic order, organized by the source of the information (e.g., laboratory, radiology). This study evaluates the functionality and utility of a knowledge-based system that generates concept-oriented views (organized around clinical concepts such as disease or organ system) of clinical data. DESIGN: The authors have developed a system that uses a knowledge base of interrelationships between medical concepts to infer relationships between data in electronic medical records. They use these inferences to produce summaries, or views, of the data that are relevant to a specific concept of interest. They evaluated the ability of the system to select relevant information, reduce information overload, and support physician information retrieval. MEASUREMENTS: The sensitivity and specificity of the system for identifying relevant patient information were calculated. Effect on information overload was assessed by comparing the amount of information in each view with the amount of information in the entire record. Information retrieval accuracy and cost (time) were used to measure the effect of using concept-oriented views on the efficiency and effectiveness of retrievals. RESULTS: The sensitivity and specificity of the system for identifying relevant clinical information were generally in the range of 70 to 80 percent. Concept-oriented views are effective in reducing the amount of information retrieved (over 80 percent reduction) and, compared with source-oriented views, are able to improve physician retrieval accuracy (p=0.04). CONCLUSION: Computer-generated, concept-oriented views can be used to reduce clinician information overload and improve the accuracy of clinical data retrieval.

Artificial Intelligence↗
PubMed2005

Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories.

With the human Plasma Proteome Project (PPP) pilot phase completed, the largest and most ambitious proteomics experiment to date has reached its first milestone. The correspondingly impressive amount of data that came from this pilot project emphasized the need for a centralized dissemination mechanism and led to the development of a detailed, PPP specific data gathering infrastructure at the University of Michigan, Ann Arbor as well as the protein identifications database project at the European Bioinformatics Institute as a general proteomics data repository. One issue that crept up while discussing which data to store for the PPP concerns whether the raw, binary data coming from the mass spectrometers should be stored, or rather the more compact and already significantly processed peak lists. As this debate is not restricted to the PPP but relates to the proteomics community in general, we will attempt to detail the relative merits and caveats associated with centralized storage and dissemination of raw data and/or peak lists, building on the extensive experience gained during the PPP pilot phase. Finally, some suggestions are made for both immediate and future storage of MS data in public repositories.

Computational Biology↗
PubMed2005

The role of informatics in the coordinated management of biological resources collections.

The term 'biological resources' is applied to the living biological material collected, held and catalogued in culture collections: bacterial and fungal cultures; animal, human and plant cells; viruses; and isolated genetic material. A wealth of information on these materials has been accumulated in culture collections, and most of this information is accessible. Digitalisation of data has reached a high level; however, information is still dispersed. Individual and coordinated approaches have been initiated to improve accessibility of biological resource centres, their holdings and related information through the Internet. These approaches cover subjects such as standardisation of data handling and data accessibility, and standardisation and quality control of laboratory procedures. This article reviews some of the most important initiatives implemented so far, as well as the most recent achievements. It also discusses the possible improvements that could be achieved by adopting new communication standards and technologies, such as web services, in view of a deeper and more fruitful integration of biological resources information in the bioinformatics network environment.

Animals↗
PubMed1999

Evaluation of a system to identify relevant patient information and its impact on clinical information retrieval.

Concept-oriented views of electronic medical records are desirable, yet difficult to create. We have developed a system that creates concept-oriented views by identifying relevant patient information, however, previous such systems have received little evaluation. We present here an evaluation of our system's ability to identify relevant patient data and generate concept-oriented views, along with the clinical impact of the generated views. The evaluation was carried out in three parts: First, using physicians and medical literature as gold standards, the system's sensitivity and specificity in identifying relevant information were measured. In some areas, the system demonstrated sensitivity comparable to that of physicians. Second, concept-oriented views were compared with original records and shown to contain significantly less non-specific information. Third, physician volunteers, when answering questions about patient cases using the concept-oriented views and traditional source-oriented views generated by the system, showed a significantly greater accuracy in information retrieval using concept-oriented views.

Clinical Laboratory Techniques↗
PubMed2001

Accessing heterogeneous sources of evidence to answer clinical questions.

The large and rapidly growing number of information sources relevant to health care, and the increasing amounts of new evidence produced by researchers, are improving the access of professionals and students to valuable information. However, seeking and filtering useful, valid information can be still very difficult. An online information system that conducts searches based on individual patient data can have a beneficial influence on the particular patient's outcome and educate the healthcare worker. In this paper, we describe the underlying model for a system that aims to facilitate the search for evidence based on clinicians' needs. This paper reviews studies of information needs of clinicians, describes principles of information retrieval, and examines the role that standardized terminologies can play in the integration between a clinical system and literature resources, as well as in the information retrieval process. The paper also describes a model for a digital library system that supports the integration of clinical systems with online information sources, making use of information available in the electronic medical record to enhance searches and information retrieval. The model builds on several different, previously developed techniques to identify information themes that are relevant to specific clinical data. Using a framework of evidence-based practice, the system generates well-structured questions with the intent of enhancing information retrieval. We believe that by helping clinicians to pose well-structured clinical queries and including in them relevant information from individual patients' medical records, we can enhance information retrieval and thus can improve patient-care.

Computational Biology↗
PubMed1981

Access to data and the information explosion: oral contraceptives and risk of cancer.

This report describes a technically feasible method to deal with the enormous volume of literature published regarding oral contraceptives. This subject was discussed in 3735 publications during the period from November 1977 through October 1980. Our findings showed that those papers reporting original, numeric relationships involving risk of cancer and use of oral contraceptives were one percent of the total 3735 publications. However, only seven of the 27 articles involved were authored by individuals from departments of obstetrics and gynecology. Further, only four of the 27 were published in journals devoted to obstetrics and gynecology. The analyses suggest a form of censorship taking place, in that the obstetrics/gynecology specialists do not have ready access to the primary data.

Contraceptives, Oral↗
PubMed2005

YeastHub: a semantic web use case for integrating data in the life sciences domain.

MOTIVATION: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies-including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository-to represent, store and query both metadata and data across life sciences datasets. RESULTS: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. AVAILABILITY: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org.

Biology↗