PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Database Management Systems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31Linked to original sources

Challenges of building clinical data analysis solutions.

Increasingly, owners of clinical information systems are turning to clinical data warehouses (CDWs) to store and to analyze their data. The CDW allows institutions to make better use of their clinical data that has been collected through its information systems. A CDW extracts data from these systems, transforms it into a usable form, and then allows users to view and analyze years of data across a large cross section of patient charts. Although warehouses have existed in healthcare for some time, there are relatively few institutions that maintain patient charts in a CDW. This is, in part, because of the challenges often seen when attempting to warehouse this type of data. These include integrating a diverse set of care practices and a variety of definitions for common data elements like medications, observations, treatments, units of measure, and even unique patient identifiers. In addition, these systems often struggle with a high level of inconsistent and/or incomplete data that must be cleaned up on a regular basis. Unlike other data warehouse systems, CDWs are often expected to gather data around the clock and in a manner that has minimum impact to the performance of the source Clinical Information Systems. Finally, CDWs often have a diverse range of clinical and administrative users. This often leads to a need for a variety of applications and/or tools for viewing and analyzing the data.

Database Management Systems↗

Ligand Depot: a data warehouse for ligands bound to macromolecules.

UNLABELLED: Ligand Depot is an integrated data resource for finding information about small molecules bound to proteins and nucleic acids. The initial release (version 1.0, November, 2003) focuses on providing chemical and structural information for small molecules found as part of the structures deposited in the Protein Data Bank. Ligand Depot accepts keyword-based queries and also provides a graphical interface for performing chemical substructure searches. A wide variety of web resources that contain information on small molecules may also be accessed through Ligand Depot. AVAILABILITY: Ligand Depot is available at http://ligand-depot.rutgers.edu/. Version 1.0 supports multiple operating systems including Windows, Unix, Linux and the Macintosh operating system. The current drawing tool works in Internet Explorer, Netscape and Mozilla on Windows, Unix and Linux.

Binding Sites↗

Computer-aided risk management--a software tool for the Hidep model.

OBJECTIVE: The Hidep risk management model has been developed and tested in clinical settings with promising results, but a tool facilitating the work has been suggested. The aim of the present study was to create and evaluate a computerized tool capable of creating overviews of the oral health situation as well as identifying risk factors and at-risk patients. The system developed should also facilitate the clinical work, for example, by assisting the user with automatic calculation of suitable Hidep groups and selection and printing of relevant patient information letters. METHOD AND MATERIALS: The system developed was based on the Hidep model, combining a number of available examination methods, risk estimation systems, and treatment suggestions. The development strategy included stepwise improvements and functionality increase based on continuous clinical applicability tests in a large international test bed. RESULTS: The results indicated that the software created was user friendly enough to be used in a common dental clinic and capable of handling the basic data of both patients and their oral health situation. The system could present useful statistics and graphs describing the overall oral health situation and identifying relevant risk groups and risk factors, based on virtually unlimited parameter combinations. CONCLUSION: The computer system developed seems to be an important step toward the possibility of creating a close-to-the-clinic model for oral health care management based on actual and locally derived patient data and risk factors. The results of this project encourage further studies of the Hidep model and its computer support.

Computer Systems↗

A bioinformatics framework for genotype-phenotype correlation in humans with Marfan syndrome caused by FBN1 gene mutations.

Mutations in the human FBN1 gene are known to be associated with the Marfan syndrome, an autosomal dominant inherited multi-systemic connective tissue disorder. However, in the absence of solid genotype-phenotype correlations, the identification of an FBN1 mutation has only little prognostic value. We propose a bioinformatics framework for the mutated FBN1 gene which comprises the collection, management, and analysis of mutation data identified by molecular genetic analysis (DHPLC) and data of the clinical phenotype. To query our database at different levels of information, a relational data model, describing mutational events at the cDNA and protein levels, and the disease's phenotypic expression from two alternative views, was implemented. For database similarity requests, a query model which uses a distance measure based on log-likelihood weights for each clinical manifestation, was introduced. A data mining strategy for discovering diagnostic markers, classification and clustering of phenotypic expressions was provided which enabled us to confirm some known and to identify some new genotype-phenotype correlations.

Computational Biology↗

GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines.

The Guideline Interchange Format (GLIF) is a model for representation of sharable computer-interpretable guidelines. The current version of GLIF (GLIF3) is a substantial update and enhancement of the model since the previous version (GLIF2). GLIF3 enables encoding of a guideline at three levels: a conceptual flowchart, a computable specification that can be verified for logical consistency and completeness, and an implementable specification that is intended to be incorporated into particular institutional information systems. The representation has been tested on a wide variety of guidelines that are typical of the range of guidelines in clinical use. It builds upon GLIF2 by adding several constructs that enable interpretation of encoded guidelines in computer-based decision-support systems. GLIF3 leverages standards being developed in Health Level 7 in order to allow integration of guidelines with clinical information systems. The GLIF3 specification consists of an extensible object-oriented model and a structured syntax based on the resource description framework (RDF). Empirical validation of the ability to generate appropriate recommendations using GLIF3 has been tested by executing encoded guidelines against actual patient data. GLIF3 is accordingly ready for broader experimentation and prototype use by organizations that wish to evaluate its ability to capture the logic of clinical guidelines, to implement them in clinical systems, and thereby to provide integrated decision support to assist clinicians.

Artificial Intelligence↗

Enhancing HMM-based biomedical named entity recognition by studying special phenomena.

The purpose of this research is to enhance an HMM-based named entity recognizer in the biomedical domain. First, we analyze the characteristics of biomedical named entities. Then, we propose a rich set of features, including orthographic, morphological, part-of-speech, and semantic trigger features. All these features are integrated via a Hidden Markov Model with back-off modeling. Furthermore, we propose a method for biomedical abbreviation recognition and two methods for cascaded named entity recognition. Evaluation on the GENIA V3.02 and V1.1 shows that our system achieves 66.5 and 62.5 F-measure, respectively, and outperforms the previous best published system by 8.1 F-measure on the same experimental setting. The major contribution of this paper lies in its rich feature set specially designed for biomedical domain and the effective methods for abbreviation and cascaded named entity recognition. To our best knowledge, our system is the first one that copes with the cascaded phenomena.

Abbreviations as Topic↗

Hierarchical data security in a Query-By-Example interface for a shared database.

Whenever a shared database resource, containing critical patient data, is created, protecting the contents of the database is a high priority goal. This goal can be achieved by developing a Query-By-Example (QBE) interface, designed to access a shared database, and embedding within the QBE a hierarchical security module that limits access to the data. The security module ensures that researchers working in one clinic do not get access to data from another clinic. The security can be based on a flexible taxonomy structure that allows ordinary users to access data from individual clinics and super users to access data from all clinics. All researchers submit queries through the same interface and the security module processes the taxonomy and user identifiers to limit access. Using this system, two different users with different access rights can submit the same query and get different results thus reducing the need to create different interfaces for different clinics and access rights.

Computer Security↗

Database of C-glycosylporphyrins in Web fashion.

The aim of this work was to organize chemical data in a client-server environment using Database Management System and Web fashion for the client interface. To solve this ancient problem (for us) merging text data, reaction schemes, tridimensional structures, and NMR, CD, and UV spectra images, we have based our implementation on a few fundamental points: no cost for the user, availability of data via the Internet, standard and freeware software, and a Web browser for the database inquiry. These functions are delivered in a platform-independent manner via the Internet and are used by computational experts and nonexperts alike. C-Glycosylporphyrins is the class of compounds chosen to test our applications. These results can be exportable for many other classes of chemical compounds.

Databases, Factual↗

MaxBench: evaluation of sequence and structure comparison methods.

SUMMARY: MaxBench is a web-based system available for evaluating the results of sequence and structure comparison methods, based on the SCOP protein domain classification. The system makes it easy for developers to both compare the overall performance of their methods to standard algorithms and investigate the results of individual comparisons. AVAILABILITY: http://www.sanger.ac.uk/Users/lp1/MaxBench/

Algorithms↗

Data integration and visualization system for enabling conceptual biology.

MOTIVATION: Integration of heterogeneous data in life sciences is a growing and recognized challenge. The problem is not only to enable the study of such data within the context of a biological question but also more fundamentally, how to represent the available knowledge and make it accessible for mining. RESULTS: Our integration approach is based on the premise that relationships between biological entities can be represented as a complex network. The context dependency is achieved by a judicious use of distance measures on these networks. The biological entities and the distances between them are mapped for the purpose of visualization into the lower dimensional space using the Sammon's mapping. The system implementation is based on a multi-tier architecture using a native XML database and a software tool for querying and visualizing complex biological networks. The functionality of our system is demonstrated with two examples: (1) A multiple pathway retrieval, in which, given a pathway name, the system finds all the relationships related to the query by checking available metabolic pathway, transcriptional, signaling, protein-protein interaction and ontology annotation resources and (2) A protein neighborhood search, in which given a protein name, the system finds all its connected entities within a specified depth. These two examples show that our system is able to conceptually traverse different databases to produce testable hypotheses and lead towards answers to complex biological questions.

Computational Biology↗

PROTEIOS: an open source proteomics initiative.

SUMMARY: PROTEIOS is an initiative for the development of a comprehensive open source system for storage, organization, analysis and annotation of proteomics experiments. The PROTEIOS platform is based on commonly acknowledged principles for proteomics data publishing. AVAILABILITY: http://www.proteios.org

Algorithms↗

PROPHET--a national computing resource for life science research.

PROPHET is a national computing resource tailored to meet the data management and analysis needs of life scientists working in a wide variety of disciplines, ranging from pharmacology to molecular biology. The PROPHET system offers a fully integrated graphics-oriented environment designed for the manipulation and analysis of tabular data, graphs, molecular structures, biological simulation models, and protein and nucleic acid sequences, and it includes access to molecular structure and sequence databases.

Computer Communication Networks↗

A data preprocessing framework for supporting probability-learning in dynamic decision modeling in medicine.

Data preprocessing is needed when real-life clinical databases are used as the data sources to learn the probabilities for dynamic decision models. Data preprocessing is challenging as it involves extensive manual effort and time in developing the data operation scripts. This paper presents a framework to facilitate automated and interactive generation of the problem-specific data preprocessing scripts. The framework has three major components: 1) A model parser that parses the decision model definition, 2) A graphical user interface that facilitates the interaction between the user and the system, and 3) A script generator that automatically generates the specific database scripts for the data preprocessing. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the clinical domain. Preliminary results demonstrate the practical promise of the framework.

Artificial Intelligence↗

PDB-Metrics: a web tool for exploring the PDB contents.

PDB-Metrics (http://sms.cbi.cnptia.embrapa.br/SMS/pdb_metrics/index.html) is a component of the Diamond STING suite of programs for the analysis of protein sequence, structure and function. It summarizes the characteristics of the collection of protein structure descriptions deposited in the Protein Data Bank (PDB) and provides a Web interface to search and browse the PDB, using a variety of alternative criteria. PDB-Metrics is a powerful tool for bioinformaticians to examine the data span in the PDB from several perspectives. Although other Web sites offer some similar resources to explore the PDB contents, PDB-Metrics is among those with the most complete set of such facilities, integrated into a single Web site. This program has been developed using SQLite, a C library that provides all the query facilities of a database management system.

Computer Graphics↗

The construction of web database server-client system for functional food factors.

In food, other than known nutrients, such as lipid, carbohydrate, protein, vitamins, and minerals, many substances with physiological function and medicinal action exist, and it is contributing to healthy improvement and/or prevention of illness. Although carotenoid, flavonoid and polyphenol, terpenoid, volatile substance and sulfur compounds, peptide, etc. have the function of illness prevention, and research of those non-nutrient functional food factors (FFF) became globally active, the research of this field is not yet done systematically. We evaluate function of FFF and reappraise known knowledge, and this knowledge is standardized and accumulated, aimed at building a web database server-client system which is easy to use for the people and nutritional research. We also collected related data such as chemical characters of FFF from literatures and other source, and formatted them into the database. We constructed the web database server-client system with MySQL database server and Apache web server based on Linux, and used Tomcat JSP engine for data connecting since they were reliable in stability and speed. We are opening the database at http://www.life-science.jp/FFF for test now.

Database Management Systems↗

An efficient and effective region-based image retrieval framework.

An image retrieval framework that integrates efficient region-based representation in terms of storage and complexity and effective on-line learning capability is proposed. The framework consists of methods for region-based image representation and comparison, indexing using modified inverted files, relevance feedback, and learning region weighting. By exploiting a vector quantization method, both compact and sparse (vector) region-based image representations are achieved. Using the compact representation, an indexing scheme similar to the inverted file technology and an image similarity measure based on Earth Mover's Distance are presented. Moreover, the vector representation facilitates a weighted query point movement algorithm and the compact representation enables a classification-based algorithm for relevance feedback. Based on users' feedback information, a region weighting strategy is also introduced to optimally weight the regions and enable the system to self-improve. Experimental results on a database of 10,000 general-purposed images demonstrate the efficiency and effectiveness of the proposed framework.

Abstracting and Indexing↗

A decision support system to meet the fluctuating needs of a hospital nursing unit.

Regardless of the care taken in generating a nursing unit staff schedule, changes in patient census and acuity as well as staff illnesses and unexpected absenteeism create unanticipated "gaps" in a schedule. Due to a lack of timely information on staff availability and nursing preferences, filling these vacancies can be costly and time consuming. We propose that by combining a revised staffing structure with an integrated database management system, a decision support system can be developed. This can enable non-management staff to make substantial time and cost saving decisions while maintaining the highest level of patient care.

Decision Support Systems, Management↗

Distributed shared memory for roaming large volumes.

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming.

Computer Graphics↗