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At least 883 records · Page 49Linked to original sources
PubMed1997

A support system for content-based medical image retrieval in object oriented databases.

This work describes both the concepts used in an Object Manager for storage of medical images as one more data type associated to objects, and a support system developed to offer this kind of tool to medical application developers. The purpose of this work is to support the retrieval of images through queries based on the graphical contents of the stored images. The usual approach uses icons and textual attributes stored with the images to specify the queries. This work uses a novel modeling technique to define the "image data type," by means of which it is possible to decide, before the query itself, the key data of each image that must be extracted from the image when it is stored in the database, so the search can be accelerated when queries are issued. This approach enables building of expansible systems, where new image processing algorithms can be added easily, using its syntactic representation stored through an Image Meta-schema into the application database schema. This work shows how such a system has been implemented, and also provides a query language used to refer and execute these algorithms from inside the database management system.

Algorithms↗
PubMed1993

Full-text document storage and retrieval in a clinical information system.

The overall design of the CIS at CPMC is heavily influenced by the decision support component. The type of automated decision support being implemented dictates the need for highly structured or coded data. The value of decision support systems has been well documented. The current reliance on free-text documents is natural and a rewarding first step to a more valuable mix of coded and free text. While the health care provider might find the textual comments of the various reports extremely useful, the capability of an automated system to vigilantly review every data element for trends and anomalies is becoming invaluable in today's ever more complex health care delivery environment. Other approaches such as optical imaging systems would facilitate human decision support, but do not supply data in a format that can be processed by automated decision support systems. The developers of the CIS at CPMC believe that data are most valuable when available for both human and automated decision support.

Clinical Medicine↗
PubMed2000

Storage and utilization of HLA genomic data--new approaches to HLA typing.

Currently available DNA-based HLA typing assays can provide detailed information about sequence motifs of a tested sample. It is still a common practice, however, for information acquired by high-resolution sequence specific oligonucleotide probe (SSOP) typing or sequence specific priming (SSP) to be presented in a low-resolution serological format. Unfortunately, this representation can lead to significant loss of useful data in many cases. An alternative to assigning allele equivalents to suchDNA typing results is simply to store the observed typing pattern and utilize the information with the help of Virtual DNA Analysis (VDA). Interpretation of the stored typing patterns can then be updated based on newly defined alleles, assuming the sequence motifs detected by the typing reagents are known. Rather than updating reagent specificities in individual laboratories, such updates should be performed in a central, publicly available sequence database. By referring to this database, HLA genomic data can then be stored and transferred between laboratories without loss of information. The 13th International Histocompatibility Workshop offers an ideal opportunity to begin building this common database for the entire human MHC.

Base Sequence↗
PubMedDate not supplied

Open source system for analyzing, validating, and storing protein identification data.

This paper describes an open-source system for analyzing, storing, and validating proteomics information derived from tandem mass spectrometry. It is based on a combination of data analysis servers, a user interface, and a relational database. The database was designed to store the minimum amount of information necessary to search and retrieve data obtained from the publicly available data analysis servers. Collectively, this system was referred to as the Global Proteome Machine (GPM). The components of the system have been made available as open source development projects. A publicly available system has been established, comprised of a group of data analysis servers and one main database server.

Computational Biology↗
PubMed2006

Statistical analysis of a database of absorption spectra of phytoplankton and pigment concentrations using self-organizing maps.

We present a statistical analysis of a large set of absorption spectra of phytoplankton, measured in natural samples collected from ocean water, in conjunction with detailed pigment concentrations. We processed the absorption spectra with a sophisticated neural network method suitable for classifying complex phenomena, the so-called self-organizing maps (SOM) proposed by Kohonen [Kohonen, Self Organizing Maps (Springer-Verlag, 1984)]. The aim was to compress the information embedded in the data set into a reduced number of classes characterizing the data set, which facilitates the analysis. By processing the absorption spectra, we were able to retrieve well-known relationships among pigment concentrations and to display them on maps to facilitate their interpretation. We then showed that the SOM enabled us to extract pertinent information about pigment concentrations normalized to chlorophyll a. We were able to propose new relationships between the fucoxanthin/Tchl-a ratio and the derivative of the absorption spectrum at 510 nm and between the Tchl-b/Tchl-a ratio and the derivative at 640 nm. Finally, we demonstrate the possibility of inverting the absorption spectrum to retrieve the pigment concentrations with better accuracy than a regression analysis using the Tchl-a concentration derived from the absorption at 440 nm. We also discuss the data coding used to build the self-organizing map. This methodology is very general and can be used to analyze a large class of complex data.

Algorithms↗
PubMed1997

The impact of anticipatory patient data displays on physician decision making: a pilot study.

Computerized patient records have long offered the promise of facilitated access to patient data for clinical decision-making. Nonetheless, the decision process benefits of improved patient data access have been poorly quantified by prior informatics research. We conducted a pilot study to test the feasibility of study methods and gather data for the planning of a future clinical trial designed to assess the impact of patient data summary displays on serum lipid test interpretation time, on targeted data retrieval time for related data, and on decision quality. The pilot demonstrated feasibility and high face validity of the decision-making simulation methods used. Problem-focused patient data summaries appear to reduce time-based decision performance measures by 40-50%, and may improve decision quality even without the inclusion of knowledge-based recommendations or guideline representations.

Data Display↗
PubMed1995

Building a medical multimedia database system to integrate clinical information: an application of high-performance computing and communications technology.

The rapid growth of diagnostic-imaging technologies over the past two decades has dramatically increased the amount of nontextual data generated in clinical medicine. The architecture of traditional, text-oriented, clinical information systems has made the integration of digitized clinical images with the patient record problematic. Systems for the classification, retrieval, and integration of clinical images are in their infancy. Recent advances in high-performance computing, imaging, and networking technology now make it technologically and economically feasible to develop an integrated, multimedia, electronic patient record. As part of The National Library of Medicine's Biomedical Applications of High-Performance Computing and Communications program, we plan to develop Image Engine, a prototype microcomputer-based system for the storage, retrieval, integration, and sharing of a wide range of clinically important digital images. Images stored in the Image Engine database will be indexed and organized using the Unified Medical Language System Metathesaurus and will be dynamically linked to data in a text-based, clinical information system. We will evaluate Image Engine by initially implementing it in three clinical domains (oncology, gastroenterology, and clinical pathology) at the University of Pittsburgh Medical Center.

Abstracting and Indexing↗
PubMed2005

DynGO: a tool for visualizing and mining of Gene Ontology and its associations.

BACKGROUND: A large volume of data and information about genes and gene products has been stored in various molecular biology databases. A major challenge for knowledge discovery using these databases is to identify related genes and gene products in disparate databases. The development of Gene Ontology (GO) as a common vocabulary for annotation allows integrated queries across multiple databases and identification of semantically related genes and gene products (i.e., genes and gene products that have similar GO annotations). Meanwhile, dozens of tools have been developed for browsing, mining or editing GO terms, their hierarchical relationships, or their "associated" genes and gene products (i.e., genes and gene products annotated with GO terms). Tools that allow users to directly search and inspect relations among all GO terms and their associated genes and gene products from multiple databases are needed. RESULTS: We present a standalone package called DynGO, which provides several advanced functionalities in addition to the standard browsing capability of the official GO browsing tool (AmiGO). DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations. The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. CONCLUSION: We have presented a standalone package DynGO that provides functionalities to search and browse GO and its association databases as well as several additional functions such as batch retrieval and semantic retrieval. The complete documentation and software are freely available for download from the website http://biocreative.ifsm.umbc.edu/dyngo.

Computer Graphics↗
PubMed1977

WHO activities in oral epidemiology.

Standard methods to facilitate the collection of data on a global basis have been developed by WHO. Data collection in accordance with criteria proposed by WHO began in 1969 from existing sources and was subsequently supplemented by new data collected using the standard methods. Associated with these methods developments, a WHO Global Oral Epidemiology program was begun with the objective of facilitating comparison of data and their use in planning, replanning, and evaluating oral health services according to needs and economic possibilities. That program provides an orderly storage and retrieval system and a visual representation of contrasts in prevalence of those oral diseases which are among the most common known to man. In selecting data for inclusion in the WHO oral epidemiology data bank, a liberal policy has been pursued to make maximum use of available material. The system of classification allows for data retrieval at various levels and for specific ages. Data on caries are available for 95 countries and on periodontal diseases for 50 countries.

Adolescent↗
PubMed1987

[A data processing system for bacteriological and chemical water analysis].

Using the "Natural" computer language a menu-guided system for cataloguing, processing and evaluating bacteriological and chemical water analyses was designed. The program can be employed to different blocs of analyses, e.g. "TrinkwV"-analyses, standard-analyses, those on volatile chlorinated hydrocarbons and bacteriological water analyses as well. For each water sample the actual, the last and the next to the last value, also arithmetical means, minimal and maximal are stored and can be retrieved. The evaluation of the bacteriological analyses and those of the volatile chlorinated hydrocarbons is carried out by a choice of text variants, whereas the TVO- and standard-analyses are interpreted automatically. Managing laboratory data has become much easier during our three years experience using this system for information storage, search and retrieval in water research and routine; even untrained users are able to handle it after a short period of tuition.

Bacteria↗
PubMed2006

Nearest neighbors by neighborhood counting.

Finding nearest neighbors is a general idea that underlies many artificial intelligence tasks, including machine learning, data mining, natural language understanding, and information retrieval. This idea is explicitly used in the k-nearest neighbors algorithm (kNN), a popular classification method. In this paper, this idea is adopted in the development of a general methodology, neighborhood counting, for devising similarity functions. We turn our focus from neighbors to neighborhoods, a region in the data space covering the data point in question. To measure the similarity between two data points, we consider all neighborhoods that cover both data points. We propose to use the number of such neighborhoods as a measure of similarity. Neighborhood can be defined for different types of data in different ways. Here, we consider one definition of neighborhood for multivariate data and derive a formula for such similarity, called neighborhood counting measure or NCM. NCM was tested experimentally in the framework of kNN. Experiments show that NCM is generally comparable to VDM and its variants, the state-of-the-art distance functions for multivariate data, and, at the same time, is consistently better for relatively large k values. Additionally, NCM consistently outperforms HEOM (a mixture of Euclidean and Hamming distances), the "standard" and most widely used distance function for multivariate data. NCM has a computational complexity in the same order as the standard Euclidean distance function and NCM is task independent and works for numerical and categorical data in a conceptually uniform way. The neighborhood counting methodology is proven sound for multivariate data experimentally. We hope it will work for other types of data.

Algorithms↗
PubMed2002

READ: RIKEN Expression Array Database.

READ, the RIKEN Expression Array Database, is a database of expression profile data from the RIKEN mouse cDNA microarray. It stores the microarray experimental data and information, and provides Web interfaces for researchers to use to retrieve, analyze and display their data. The goals for READ are to serve as a storage site for microarray data from ongoing research in the RIKEN mouse encyclopedia project and to provide useful links and tools to decipher biologically important information. The gene information is based mainly on the fully annotated FANTOM database. READ can be accessed at http://read.gsc.riken.go.jp/. READ also provides a search tool [READ integrates gene expression neighbor (RINGENE)] for genes with similarities in expression profiling.

Animals↗
PubMed1998

Data base and management system for clinical positron emission tomography (PET) studies.

A data base and management system connected to an image analysis system has been developed and utilized for clinical positron emission tomography (PET). This data base system, 1) is based on "GBASE", a general purpose data base, which runs on a UNIX work station, 2) works on a network file system and is connected to PET cameras and other data acquisition devices as well as to an image analysis system "Dr.View", 3) centrally manages the data stored in a data storage unit, 4) is easily modifiable and expandable, and 5) has a human friendly interface which requires minimum operation for registration, retrieval and management. We have been using this system to handle clinical PET data for seven years and have optimized the data base schema. As a result, this system has become a truly practical tool for the daily operation and is well-received by technologists, nuclear physicians and attending physicians.

Brain↗
PubMed1991

Sports injury registration: the Fysion Blesreg system.

Fysion Blesreg is a new system on which sports assistants (trainers, masseurs, physiotherapists and physicians) can rely for quick and straightforward registration and retrieval of personalized injury data. Registration of injury data can provide a clear picture of the injury mechanism, which in turn can lead to effective preventive measures and a decline in sports injuries. The two components of the Fysion Blesreg system are registration forms and computer software. Registration forms are filled out when the competition starts (zero form), and when injuries occur (team cards and players' cards). Data are collected for the individual (zero form), the sports activity (team card), and the cause, nature and treatment of the injury (player's card). All data are entered into the computer with an MS-DOS based computer program, and can in various ways be reported or graphically reproduced.

Athletic Injuries↗
PubMed1992

Software suite for image archiving and retrieval.

The efficient operation of a clinical picture archiving and communication system (PACS) requires a fully functional image archive. The archive should not only be able to store and retrieve images reliably but should also work in concert with software that optimizes the flow of image-related information throughout the PACS. The authors devised a software suite that serves to improve the flow and content of information and the integrity of the data. The software was developed by translating the functions performed by a conventional film library. Types of transactions possible with this system include scheduling, canceling, rescheduling, and prestaging examinations; changing demographic information; merging patient information; and generating reports. The authors believe such a software suite is essential for a clinically useful PACS.

Data Display↗