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At least 1,333 records · Page 74Linked to original sources
PubMed2003

Optimizing query response with XML user profile in mobile clinical systems.

Improvements of modern mobile technology, have created a need for a mobile clinical environment. In the field of mobile clinical systems, getting information on time is as important as mission critical aspects. However, web access time with the mobile device is still not feasible clinically. Therefore, the optimisation of query response becomes an important issue. We have developed a query optimising method using a user profile. We analysed user (clinician) specific queries in the medical field. Most of the data retrieval in the medical field is focused on the clinical test results, and the patient inverted exclamation mark s demographic information. Sometimes the information requested in the medical field places a heavy load on the database, since such information may require full database scanning and much joining of tables in the databases. In such cases, constructing profile data and employing it for data retrieval would help to improve the response time. The use of a predefined profile avoids the multiple joining process, and shortens the total response time. The object of our research is to improve query response by creating user profiles and using this profile information for patient data retrieval.

Hospital Information Systems↗
PubMedDate not supplied

[The system of collection, processing, storage and retrieval of x-ray diagnostic images].

The paper describes a system able to combine conventional techniques of diagnostic x-ray imaging with direct digital imaging on the original receiver with a resolution of 1.2 lin/mm. Digital roentgenography may be introduced into medical practice basing on the system of computers at the working places of roentgenologist and his assistant. Data base of long-term storage of x-ray images and input software for each x-ray picture are outlined. The authors have some experience of utilizing the system in the random sequence of patients (20,000) in general and specialized hospitals of Novosibirsk.

Databases as Topic↗
PubMed2004

Applying data mining techniques to library design, lead generation and lead optimization.

Many data mining techniques have been applied to activity and ADMET datasets and the resulting models are being used to understand quantitative structure-activity relationships and design new libraries. This review summarizes data mining concepts and discuss their application to library design, lead generation (particularly for sequential screening) and lead optimization (specifically for generating and interpreting QSAR models). Also, this review discusses recent comparative studies between data mining techniques and draws some conclusions about the patterns emerging in the drug discovery data mining field.

Algorithms↗
PubMed2006

Density codes and shape spaces.

This paper presents an algorithm that allows for encoding probability density functions associated to samples of points of R(n). The resulting code is a sequence of points of R(n) whose density function approximates that of the set of data points. However, contrarily to sampled data points, code points associated to two different density functions can be matched, which allows to efficiently compare such functions. Moreover, the comparison of two codes can be made invariant to a wide variety of geometrical transformations of the support coordinates, provided that the Jacobian matrix of the transformation be everywhere triangular, with a strictly positive diagonal. Such invariances are commonly encountered in visual shape recognition, for example. Thus, using this tool, one can build spaces of shapes that are suitable input spaces for pattern recognition and pattern analysis neural networks. Moreover, a parallel neural implementation of the encoding algorithm is available for 2D image data.

Algorithms↗
PubMed2006

Growing hierarchical tree SOM: an unsupervised neural network with dynamic topology.

In this paper we introduce a tree structured self-organizing network, called the Growing Hierarchical Tree SOM (GHTSOM), that combines unsupervised learning with a dynamic topology for hierarchical classification of unlabelled data sets. The main feature of the proposed model is a SOM-like self-organizing process that allows the network to adapt the topology of each layer of the hierarchy to the characteristics of the training set. In particular the self-organization is obtained in two steps: the first one concerns the learning phase and is finalized with the creation of a tree of SOMs, while the second one is in regard to the clustering phase and provides the formation of classes for each level of the tree (hence self-organization not only for training but also for the creation of topological connections). As a result the network works without the need for user-defined parameters. Experimental results are proposed on both synthetic and real data sets.

Algorithms↗
PubMedDate not supplied

Clinical and pharmacogenomic data mining: 3. Zeta theory as a general tactic for clinical bioinformatics.

A new approach, a Zeta Theory of observations, data, and data mining, is being forged from a theory of expected information into an even more cohesive and comprehensive form by the challenge of general genomic, pharmacogenomic, and proteomic data. In this paper, the focus is not on studies using the specific tool FANO (CliniMiner) but on extensions to a new broader theoretical approach, aspects of which can easily be implemented into, or otherwise support, excellent existing methods, such as forms of multivariate analysis and IBM's product Intelligent Miner. The theory should perhaps be distinguished from an existing purely number-theoretic area sometimes also known as Zeta Theory, which focuses on the Riemann Zeta Function and the ways in which it governs the distribution of prime numbers. However, Zeta Theory as used here overlaps heavily with it and actually makes use of these same matters. The distinction is that it enters from a Bayesian information theory and data representation perspective. It could thus be considered an application of the 'mathematician's version'. The application is by no means confined to areas of modern biomedicine, and indeed its generality, even merging into quantum mechanics, is a key feature. Other areas with some similar challenges as modern biology, and which have inspired data mining methods such as IBM's Intelligent Miner, include commerce. But for several reasons discussed, modern molecular biology and medicine seem particularly challenging, and this relates to the often irreducible high dimensionality of the data. This thus remains our main target.

Computational Biology↗
PubMed2006

The Evolving Tree--analysis and applications.

In this paper, we enhance and analyze the Evolving Tree (ETree) data analysis algorithm. The suggested improvements aim to make the system perform better while still maintaining the simple nature of the basic algorithm. We also examine the system's behavior with many different kinds of tests, measurements and visualizations. We compare the ETree's performance against classical data analysis methods and very similar modern systems. We find that the ETree is a suitable method for unsupervised analysis of huge data sets.

Algorithms↗
PubMed2000

Picture archiving and communication systems.

Picture archiving and communication systems (PACS) are extremely versatile systems that facilitate the transfer of digital images and patient data throughout a healthcare enterprise. PACS are most commonly used in radiology departments to process images from diagnostic imaging modalities, such as digital radiography devices and magnetic resonance imaging (MRI) systems. In this article, we evaluate three such systems from three of the largest PACS suppliers--the Agfa IMPAX, GE PathSpeed, and Siemens Sienet. The ultimate goal of any PACS is to improve workflow within the enterprise. Our testing focused on whether, and to what degree, the systems could meet this goal. We found that all three PACS are fairly complete and able to support image distribution and improve workflow compared with film-based processes. However, we did identify significant differences--along with some noteworthy limitations--with respect to system design and operation, external integration capabilities, and supplier support and professional services. We have ranked the systems for each of these factors to help healthcare facilities identify the system that will best meet their needs. Also in this Evaluation, we present an overview of the technology, a Glossary of PACS terminology (see page 400), selection guidance, and discussions of PACS-related topics, including data compression options, the role of the DICOM standard, and concerns about data security in many of today's systems.

Automation↗
PubMed2001

HPARSER: extracting formal patient data from free text history and physical reports using natural language processing software.

A prototype, HPARSER, processes a patient history and physical report such that specific data are obtained and stored in a patient data record. HPARSER is a recursive transition network (RTN) parser, and includes English and medical grammar rules, lexicon, and database constraints. Medical grammar rules augment the grammar rule base and specify common phrases seen in patient reports (e.g., "pupils are equal and reactive"). Each database constraint associates a grammar rule with a database table and attribute. Constraint behavior is such that if a rule is satisfied, data is extracted from the parse tree and stored into the database. Control reports guided construction of grammar and constraint rules. Test reports were processed with the control rules. 85% of test report sentences parsed and a 60% data capture rate, compared to controls, was achieved. HPARSER demonstrates use of an RTN to parse patient reports, and database constraints to transfer formal data from parse trees into a database.

Humans↗
PubMed1996

The PEN&PAD data entry system: from prototype to practical system.

This paper describes some of the issues addressed in the transition of the PEN&PAD from prototype clinical workstation to practical data entry system for use by general practitioners in the UK. Background and motivation of the PEN&PAD and GALEN projects are presented before the operation of the PEN&PAD user interface is described. A number of issues which have arisen in the development of the PEN&PAD Data Entry System are discussed.

Humans↗
PubMed2002

ExInt: an Exon Intron Database.

The Exon/Intron Database (ExInt) stores information of all GenBank eukaryotic entries containing an annotated intron sequence. Data are available through a retrieval system, as flat-files and as a MySQL dump file. In this report we discuss several implementations added to ExInt, which is accessible at http://intron.bic.nus.edu.sg/exint/newexint/exint.html.

Animals↗
PubMed2002

Introducing an academic data warehouse into the undergraduate medical curriculum.

There is increasing interest in integrating population health and informatics topics into the undergraduate medical curriculum, yet little consensus exists on the most effective approach to accomplish this. We introduced the use of an academic data warehouse of encrypted patient information into an existing 2nd year medical school course. Exercises were developed requiring students to retrieve and interpret information regarding local disease prevalence, practice patterns, and patient characteristics. These exercises were integrated into existing weekly problem sets in a multiple-choice format. Faculty and student perceptions were assessed with surveys, and augmented with interviews of student volunteers, and database usage statistics. Our results indicate widespread agreement among both students and faculty that population-based medicine warrants inclusion in undergraduate medical education. The majority of the students felt the exercises complemented the clinical cases around which they were structured. There was less agreement, however, that the exercises were valuable, with several students suggesting a more open-ended, discussion-oriented approach. It was clear that faculty perceptions had a significant impact on student reactions.

Attitude to Computers↗
PubMed2004

Consequences of impaired data quality on information retrieval in electronic patient records.

OBJECTIVES: To assess the quality of specific information in electronic patient records and the consequences of sub-optimal data quality on automated information retrieval. METHODS: Patient records were evaluated with respect to accuracy of data relevant for retrieval according to a source-oriented, time-oriented and concept-oriented view of the record. Retrieval effectiveness was estimated using various methods based on record structure, text based retrieval and combinations of these. RESULTS: 98.1% of record documents were consistent regarding author, 99.8% regarding department of origin and 90.9% regarding document date. Document type was definitely not consistent in 8% of the documents. Estimated recall was 97% with 50% precision for document retrieval on the basis of date, and varying from 31 to 100% for retrieval based on document type. Retrieval based on manually supplied semantic tags performed better than simple string-based methods and improved when combined with string-matching mechanisms. CONCLUSIONS: Data attributes central for automated document retrieval in electronic patient records showed variable accuracy, with potentially negative consequences for basic record navigation. Text-based retrieval was inferior to methods based on data representing record structure. Quality of specific information elements suffered from lack of precise definitions and adequate mechanisms for quality assurance.

Information Storage and Retrieval↗
PubMed1995

Computer assisted data analysis in intensive care: the ICDEV project--development of a scientific database system for intensive care (Intensive Care Data Evaluation Project).

INTRODUCTION: Patient Data Management Systems (PDMS) for ICUs collect, present and store clinical data. Various intentions make analysis of those digitally stored data desirable, such as quality control or scientific purposes. The aim of the Intensive Care Data Evaluation project (ICDEV), was to provide a database tool for the analysis of data recorded at various ICUs at the University Clinics of Vienna. SETTINGS: General Hospital of Vienna, with two different PDMSs used: CareVue 9000 (Hewlett Packard, Andover, USA) at two ICUs (one medical ICU and one neonatal ICU) and PICIS Chart+ (PICIS, Paris, France) at one Cardiothoracic ICU. CONCEPT AND METHODS: Clinically oriented analysis of the data collected in a PDMS at an ICU was the beginning of the development. After defining the database structure we established a client-server based database system under Microsoft Windows NI and developed a user friendly data quering application using Microsoft Visual C++ and Visual Basic; RESULTS: ICDEV was successfully installed at three different ICUs, adjustment to the different PDMS configurations were done within a few days. The database structure developed by us enables a powerful query concept representing an 'EXPERT QUESTION COMPILER' which may help to answer almost any clinical questions. Several program modules facilitate queries at the patient, group and unit level. Results from ICDEV-queries are automatically transferred to Microsoft Excel for display (in form of configurable tables and graphs) and further processing. CONCLUSIONS: The ICDEV concept is configurable for adjustment to different intensive care information systems and can be used to support computerized quality control. However, as long as there exists no sufficient artifact recognition or data validation software for automatically recorded patient data, the reliability of these data and their usage for computer assisted quality control remain unclear and should be further studied.

Austria↗
PubMed2006

A technique for identifying three diagnostic findings using association analysis.

In diagnosing diseases in clinical practice, a combination of three clinical findings is often used to represent each disease. This is largely because it is often difficult or impractical to assess for all possible combinations of symptoms and abnormal exam findings that occur in any particular disease. For most diseases, diagnostic triads are based on empirical observations. In this study, we determined diagnostic triads for chronic diseases using data mining procedures. We also verified the combinations' validity as well as our procedure for determining them. We used symptoms and examination findings from 477 patients with chronic diseases, collected as part of a 35-year longitudinal study begun in 1968. For each patient there were 295 items from examinations in internal medicine, dermatology, ophthalmology, dentistry and blood tests. We judged each item to be either normal or abnormal, and restricted the analysis to the abnormal findings. To analyze such an exhaustive assortment, we used the data mining technique of association analysis. The analysis generated three clinical findings for each disease. Diseases were defined based on blood tests. Searching through all 295 items to find the three most useful clinical findings would be impractical on a commodity PC. However, by excluding normal items, we were able to sufficiently reduce the total number of combinations so as to make combinatorial analysis on a PC feasible. In addition to more accurate diagnoses, we believe our technique can identify those diagnostic data that are more cost effective in terms of time and other resources required for their collection.

Data Collection↗
PubMed1996

An epilepsy information system to support routine and research.

An epilepsy information system is described that supports routine patient care, research, and medical management. The patient's clinical data is ordered in time by the date of the patient contact when the data was collected. The clinical data is also classified into six categories. An unrestricted text group has text subjects in each of these groups as well as in a general free text area. The system is integrated with other information subsystems (e.g. patient registration, clinical chemistry laboratory, EEG department and pharmacy) as well as with the routinely used text processor. Data inquiries for research and medical management purposes are programmed in a Structured Query Language (SQL). The data needed to answer these queries are taken from the data collected in daily routine. The integration of the system is very useful because data only have to be entered once and can be used when and where needed. Patient data stored in this system is more accessible in general as well as more usable for research purposes compared with the patient data previously stored only on paper.

Data Collection↗
PubMed1996

Perception of detail and greyscale range in X-ray fluoroscopy images captured with a personal computer and frame-grabber.

OBJECTIVE: To assess the dynamic range of radiological images captured with a personal computer frame-grabbing system coupled to an X-ray fluoroscopy machine. METHODS: A 386DX-40 MHz, IBM compatible, computer with an SVGA monochrome graphics subsystem and a 387 co-processor, installed with a Screen Machine frame-grabber and controlled by a program specially written was used. Various systems were examined and the observer's perceptions of the results assessed. RESULTS: The dynamic range available to an ordinary X-ray fluoroscopy system was found to be restricted to about 750 mV. Similar measurements showed that the dynamic range was always restricted to 3/4-1/2 of the full available signal because of a high value of the dark voltage of the TV camera's target on all seven systems measured. The dynamic range of the computer-frame grabber system was found to be significantly wider than the Image Intensifier-TV camera chain but, surprisingly, it was affected by the type of file format used for image storing on disk. Clinical images from a barium meal examination as well as CT images captured after optimisation of the frame-grabber were found to contain large quantities of noise in the first two least significant bit planes making them redundant and limiting the grey levels needed for image display to less than 64. This number was also less than the 80 grey levels that could be discriminated by the human eye on the computer monitor. CONCLUSIONS: It was concluded that 6 bit digitisation would have been sufficient for image capture. The advantages of the wider dynamic range of the frame-grabber and the processing capabilities of the computer were tested for the possibility of improving the perception of detail. However, the results were negative. The limiting spatial resolution measured with a variable density bar pattern at all magnifications was about 0.4 lp/mm lower from that measured directly on the fluoroscopic screen. A detail perception test had the same result. The perception success was significantly lower with the digital images at all but the highest of the exposure rates and despite the use of image processing filters.

Artifacts↗