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PubMed2000

ENVIRONMENTAL AUDITING: Patterns of Aquatic Species Imperilment in the Southern Appalachians: An Evaluation of Regional Databases.

/ For regional analyses of species imperilment patterns, data on species distributions are available from the U.S. Fish and Wildlife Service and from the state heritage programs. We compared these two different databases as sources of best available information for regional analyses of patterns of aquatic species imperilment for 132 counties in the southern Appalachians and examined patterns produced from the databases. The heritage program database contained information about a greater number of imperiled species because species need not be federally listed as threatened or endangered to be included in this database. In the southern Appalachians, about half of imperiled molluscs and about one-fourth of imperiled fish were listed as threatened or endangered; much smaller proportions of other taxonomic groups were federally listed. Most threatened and endangered species appeared on both lists, but for about 40% of the species inconsistencies exist, notably a lack of recent records in the heritage program dataset. Numbers of species in each county were significantly different between the two datasets for Georgia, Tennessee, and Virginia, where the largest number of threatened and endangered species reside. Nevertheless, some counties always appeared as centers of imperilment, and the general spatial patterns of imperilment were similar.

Journal Article↗

PubMed2002

Monitoring the accuracy of a PACS image database.

"What you don't know won't hurt you" is a proverb that does not apply to a database on which patient lives depend. One of the core components of the picture Archiving and communications system (PACS) is an image database that contains the location and state of images and their corresponding demographic information. An image associated with the wrong patient name has potentially devastating implications, especially if the error is not caught early. This article describes how Texas Children's Hospital addresses the challenge of ensuring the accuracy of data of our PACS image database. It presents the routine checks that our PACS analysts perform every three hours and on a daily and monthly basis. These include steps involved in "fixing" exam data when an examination has missing or incorrect demographic information. In addition, this report compares how our institution assured accuracy of our film-based archive before PACS. Human error is the source of most inaccuracies in the image database, and automation such as bar code scanners and DICOM Modality Work List management have decreased their frequency, but without totally eliminating them. Some errors are routinely generated by the nature of radiology imaging operations and the limitations of devices for automating those operations. For example, computed tomography exams of the head, chest, and abdomen are routinely acquired during the same scan but must be separated into different exams for interpretation by different physicians. Factors contributing to inaccurate information include major system modifications, such as software or hardware upgrades, service interruptions, inaccurate problem descriptions provided by the user to the PACS analyst, and steps taken by the PACS analyst or technologist to correct errors.

Quality Control↗

PubMed2003

Implementing a MIRC query interface for a database driven teaching file.

This paper describes the authors' experience with integrating an existing database-driven teaching file with the RSNA (Radiological Society of North America) Medical Imaging Resource Center (MIRC). MIRC is the product of an RSNA-sponsored initiative to enable medical institutions to share their electronic medical content (images, text, and multimedia) by creating a distributed repository accessible from the Internet. An existing database-driven teaching file, developed by the authors and used extensively by the University of California San Francisco (UCSF) Department of Radiology since 1998, was retrofitted to include an interface for handling broadcast queries initiated by a MIRC query service. These queries take place through the exchange of XML documents via HTTP. After all the storage services have responded, the results are collated by the query service and presented to the user. The teaching file and MIRC interface were developed using the 4th Dimension Relational Database Management System (RDBMS). The integration process primarily involved mapping the "MIRCdocument" schema to the teaching file's schema, translating the actual MIRC query into the internal query language of the database and extending the access control mechanisms of the teaching file to allow public access. A working implementation of the interface required only 3 days of development time, with refinements taking place over several months. Interface development was greatly aided by MIRC's use of well-established Internet standards. This project has demonstrated the feasibility of implementing a MIRC interface on an existing teaching file server.

Computer-Assisted Instruction↗

PubMed1982

SUMER: a database concept for clinical research and patient data-management.

A new database model is presented for patient information systems and clinical research database. Its main objective is to deal easily with the changing needs in data structure and organization and to make the model free of computing or programming related considerations. Based on the relational and entity relationship models, it allows the creation of records and files; records may belong to as many files as one wishes. Conditions introduced at the definition level make it very easy to define subfiles on selected criteria without the need to write an extraction program. A database modification step allows the reorganisation of an already existing database without any programming. Tested on several cases the model is presently at the development stage on a DEC VAX750 computer.

Computers↗

PubMed1985

Clinician use of a pediatric cardiology database on a microcomputer.

A pediatric cardiology database was designed and implemented on a microcomputer using the MEDUS/A (Harvard School of Public Health) database management system. This database has potential utility in the areas of clinical research, patient management, and administration. Initial uses of the system include a study of ventricular septal defects, and automation of pacemaker clinic and cardiac catheterization laboratory records. Clinicians with little or no programming experience can alter the database structure and tailor complicated applications to their particular needs. Preliminary evaluation of the system is presented.

Cardiac Catheterization↗

PubMed1987

Computer database of ambulatory EEG signals.

The paper describes an ambulatory EEG database. The database contains segments of AEEGs done on 45 subjects. Each epoch (1/8th second or more) of AEEG data has been annotated into 1 of 40 classes. The classes represent background activity, paroxysmal patterns and artifacts. The majority of classes have over 200 discrete epochs. The structure is flexible enough to allow additional epochs to be readily added. The database is stored on transportable media such as digital magnetic tape or hard disk and is thus available to other researchers in the field. The database can be used to design, evaluate and compare EEG signal processing algorithms and pattern recognition systems. It can also serve as an educational medium in EEG laboratories.

Adolescent↗

PubMed1994

Users conceptual views on medical information databases.

As information databases we consider all the kinds of information repositories that are handled by computer systems. When querying very large information databases, the end-users are often faced with the problem to parse their questions efficiently into the query languages of the computer systems. Conceptual graphs were initially designed for natural language analysis and understanding. Due to their closeness to semantic networks, their expressiveness is powerful enough to be applied to knowledge representation and use by computer systems. This work demonstrates that conceptual graphs are a suitable means to model both the information in patient databases and the queries to these databases, and that operations on graphs can compute the pattern matching process needed to provide the answers. A prototype that exploits this model is presented. Experiments have been made with the material furnished by the Unified Medical Language System project (version 2, 1992) of the National Library of Medicine, USA.

Abstracting and Indexing↗

PubMed1993

Knowledge discovery in biomedical databases: a machine induction approach.

The increase in the number and size of available databases by far exceeds the growth of the corresponding knowledge. Furthermore, many databases contain information which is not possessed by an existing human expert. This creates both a need and an opportunity for extracting knowledge from databases. An unsolved problem in molecular biology is the problem of predicting a protein's secondary structure from its primary structure. Inductive machine learning is a search for a plausible general description which can explain the given input data, and is useful for predicting new data. In this paper we present a statistical inductive algorithm which can be used to produce new rules for predicting multiple protein secondary structures from protein primary structure databases.

Algorithms↗

PubMed2005

Matching unknown empirical formulas to chemical structure using LC/MS TOF accurate mass and database searching: example of unknown pesticides on tomato skins.

Traditionally, the screening of unknown pesticides in food has been accomplished by GC/MS methods using conventional library searching routines. However, many of the new polar and thermally labile pesticides and their degradates are more readily and easily analyzed by LC/MS methods and no searchable libraries currently exist (with the exception of some user libraries, which are limited). Therefore, there is a need for LC/MS approaches to detect unknown non-target pesticides in food. This report develops an identification scheme using a combination of LC/MS time-of-flight (accurate mass) and LC/MS ion trap MS (MS/MS) with searching of empirical formulas generated through accurate mass and a ChemIndex database or Merck Index database. The approach is different than conventional library searching of fragment ions. The concept here consists of four parts. First is the initial detection of a possible unknown pesticide in actual market-place vegetable extracts (tomato skins) using accurate mass and generating empirical formulas. Second is searching either the Merck Index database on CD (10,000 compounds) or the ChemIndex (77,000 compounds) for possible structures. Third is MS/MS of the unknown pesticide in the tomato-skin extract followed by fragment ion identification using chemical drawing software and comparison with accurate-mass ion fragments. Fourth is the verification with authentic standards, if available. Three examples of unknown, non-target pesticides are shown using a tomato-skin extract from an actual market place sample. Limitations of the approach are discussed including the use of A + 2 isotope signatures, extended databases, lack of authentic standards, and natural product unknowns in food extracts.

Chromatography, Liquid↗

PubMed2005

Novel gas chromatography-mass spectrometry database for automatic identification and quantification of micropollutants.

A novel gas chromatography-mass spectroscopy (GC-MS) database for identification and quantification of micropollutants in environmental and food samples is reported. GC retention times, calibration curves, and mass spectra of nearly 700 chemicals were registered in the database, and the GC retention times of registered chemicals in actual samples were predicted from the retention times of n-alkanes measured before sample analysis. Differences between predicted and actual retention times were less than 3 s, an accuracy that is nearly identical to that obtained by analysis of standard substances. After the retention times were predicted, a calibration file for the GC-MS instrument was created from the predicted retention times, calibration curves, and mass spectra of the registered chemicals. With the resulting calibration file, automated identification of all the chemicals in actual samples was possible without the use of standards, and the identification method was as reliable as conventional methods. When the GC inlet, column, and tuning conditions were adjusted using GC-MS performance check standards, relative standard deviations of 20% or less for determination values could be obtained. More than 90% of the chemicals in the database could be detected at a sensitivity sufficient for all practical purposes (100 pg or less). Because each chemical in the database, to which new substances can easily be added, can be determined in 1 h, micropollutants in samples can be analyzed efficiently and inexpensively.

Calibration↗

PubMed2005

Identifying optimal incomplete phylogenetic data sets from sequence databases.

We introduce a new method for identifying optimal incomplete data sets from large sequence databases based on the graph theoretic concept of alpha-quasi-bicliques. The quasi-biclique method searches large sequence databases to identify useful phylogenetic data sets with a specified amount of missing data while maintaining the necessary amount of overlap among genes and taxa. The utility of the quasi-biclique method is demonstrated on large simulated sequence databases and on a data set of green plant sequences from GenBank. The quasi-biclique method greatly increases the taxon and gene sampling in the data sets while adding only a limited amount of missing data. Furthermore, under the conditions of the simulation, data sets with a limited amount of missing data often produce topologies nearly as accurate as those built from complete data sets. The quasi-biclique method will be an effective tool for exploiting sequence databases for phylogenetic information and also may help identify critical sequences needed to build large phylogenetic data sets.

Base Sequence↗

PubMed1996

Muscular weakness assessment: use of normal isometric strength data. The National Isometric Muscle Strength (NIMS) Database Consortium.

OBJECTIVE: Assessment of muscle strength is vital to the management of patients with muscular weakness. Clinical interpretation of isometric strength data for individual patients has been limited because of the lack of a reference population for comparison. The purpose of this study was to develop regression equations to predict maximal isometric strength based on gender, age, height, and weight. Patients' absolute strength values may then be expressed as a percentage of their predicted values, facilitating the determination of presence and extent of weakness. DESIGN: Three separate neuromuscular research groups developed databases of normal maximal isometric strength values, using standardized testing procedures. The databases were combined into a single database, and multiple regression equations were formulated for strength prediction for the 20 muscle groups tested. SETTING: Seven neuromuscular research units, each within the neurology department of a university-based teaching facility. SUBJECTS: A convenience sample of 493 volunteers who had no medical conditions that would have prohibited them from performing a maximal isometric strength test. MAIN OUTCOME MEASURE: Maximal isometric strength (kg) of ten muscle groups was measured bilaterally. RESULTS: Regression equations and 95% prediction intervals are derived from the combined database. A case study demonstrates the use of the predictive equations in determining presence and extent of weakness. CONCLUSION: Predictive strength equations facilitate assessment of muscular weakness.

Adolescent↗

PubMedDate not supplied

A review of methodologies for assessing drug effectiveness and a new proposal: randomized database studies.

The need to evaluate the effects of health technologies in clinical practice is increasingly important. In this article, we review the advantages and limitations of naturalistic randomized clinical trials (RCTs) and database analyses, the two primary methods for evaluating treatment effectiveness. Also, we comment on a newer research strategy, cross-design synthesis, which proposes the complementary use of both experimental RCTs and observational database methodologies to avoid the main weaknesses of each: respectively, the lack of external and internal validity. Finally, we propose a new strategy--randomized database studies--capable of generating results with an acceptable balance between internal and external validity. This strategy consists of the simultaneous use of both experimental and observational tools in the assessment of drugs' effectiveness. Randomization is essential to minimize comparison bias, and one possibility for such studies is that randomization modules could be included in computer-based patient records. Although we identify some of the difficulties in implementing the process, the progressive standardization of clinical practice and the development and widespread adoption of improved computer-based patient records could facilitate the use of randomized database studies as a new method of research.

Economics, Pharmaceutical↗

PubMed2005

Using an image-extended relational database to support content-based image retrieval in a PACS.

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.

Information Storage and Retrieval↗

PubMed1998

Selection of controls in database case-control studies: glucocorticoids and the risk of glaucoma.

In case-control studies conducted using computerized databases, controls are often selected as a random sample from the base population. This representative choice of controls is intended to guard against selection bias. We show, using data from a database case-control study, that such a definition of controls may also lead to selection bias under two conditions: (1) if the target disease has a prolonged asymptomatic clinical course with its detection depending on a specific physical examination and (2) if exposed patients have a higher likelihood of having the disease detected than unexposed patients. The extent of the bias that could result from the use of randomly selected controls was investigated in the context of a case-control study of the risk of ocular hypertension or glaucoma associated with the use of glucocorticoids, conducted using the Quebec universal health insurance computerized databases. This article also illustrates that a computerized database can be useful to empirically explore opportunities for bias.

Aged↗

PubMedDate not supplied

Temporal image database design for outcome analysis of lung nodule.

This paper presents the design of a temporal image database system and its application in thoracic imaging. The design of this information system is based on the client/server architecture. The system consists of a chest imaging database server, a library of image processing modules, a link to the picture archiving and communication system (PACS) archive, and a low end client workstation with motif-based graphic user interface (GUI). The database system can be used to aid the radiologists in quantitating solitary or multiple long nodules and in assessing effectiveness of therapeutic procedures for these lung cancers. The GUI allows a user to retrieve any patient study from PACS. After a nodule is visually identified, it will be segmented automatically to obtain relevant features, such as the center of mass, volume, and surface area. Such 3D nodule information, together with the patient textual information, is subsequently organized in the chest imaging database to facilitate outcome analysis.

Breast Neoplasms↗

PubMed1995

Mining genomes: correlating tandem mass spectra of modified and unmodified peptides to sequences in nucleotide databases.

The correlation of uninterpreted tandem mass spectra of modified and unmodified peptides, produced under low-energy (10-50 eV) collision conditions, with nucleotide sequences is demonstrated. In this method nucleotide databases are translated in six reading frames, and the resulting amino acid sequences are searched "on the fly" to identify and fit linear sequences to the fragmentation patterns observed in the tandem mass spectra of peptides. A cross-correlation function is then used to provide a measurement of similarity between the mass-to-charge ratios for the fragment ions predicted by amino acid sequences translated from the nucleotide database and the fragment ions observed in the tandem mass spectrum. In general, a difference greater than 0.1 between the normalized cross-correlation functions for the first- and second-ranked search results indicates a successful match between sequence and spectrum. Measurements of the deviation from maximum similarity employing the spectral reconstruction method are made. The search method employing nucleotide databases is also demonstrated on the spectra of phosphorylated peptides. Specific sites of modification are identified even though no specific information relevant to sites of modification is contained in the character-based sequence information of nucleotide databases.

Amino Acid Sequence↗

PubMedDate not supplied

Database mining using soft computing techniques. An integrated neural network-fuzzy logic-genetic algorithm approach.

Two different soft computing (SC) techniques (a competitive learning neural network and an integrated neural network-fuzzy logic-genetic algorithm approach) are employed in the analysis of a database subset obtained from the Cambridge Structural Database. The chemical problem chosen for study is relevant to the relationship between various metric parameters in transition metal imido (LnMdNZ, Z = carbon-based substituent) complexes and the chemical consequences of such relationships. The SC techniques confirmed and quantified the suspected relationship between the metal-nitrogen bond length and the metal-nitrogen-substituent bond angle for transition metal imidos: increased metal-nitrogen-carbon angles correlate with shortened metal-nitrogen distances. The mining effort also yielded an unexpected correlation between the NC distance and the MNC angle-shorter NC correlate with larger MNC. A fuzzy inference system is used to construct an MNred-NC-MNC hypersurface. This hypersurface suggests a complicated interdependence among NC, MNred, and the angle subtended by these two bonds. Also, major portions of the hypersurface are very flat, in regions where MNC is approaching linearity. The relationships are also seen to be influenced by whether the imido substituent is an alkyl or aryl group. Computationally, the present results are of particular interest in two respects. First, SC classification was able to isolate an "outlier" cluster. Identification of outliers is important as they may correspond to unreported experimental errors in the database or novel chemical entities, both of which warrant further investigation. Second, the SC database mining not only confirmed and quantified a suspected relationship (MNred versus MNC) within the data but also yielded a trend that was not suspected (NC versus MNC).

Journal Article↗