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At least 649 records · Page 36Linked to original sources
PubMed2005

Agent oriented approach to handling medical data.

Medical treatment of a patient could be represented as a circle of the following actions: examination, diagnostics, and therapy. The aims of the actions are to find out the patient's state of health and consequently to conclude about possible diseases and finally to choose a suitable therapy. In long term, the circle of actions repeat as long as the patient is not healthy. Efficiency of this treatment depends on the knowledge and the experiences of the physicians involved. Information technology offers many possibilities to help the physicians increase the efficiency and the quality of this work. In the article, we present an agent-oriented computer-based health care service, which uses information from different data sources that are physically distributed across several sites. Such a decentralized approach mirrors the organizational structure of a health service and it is very similar to an agent-oriented view of the world.

Artificial Intelligence↗
PubMed1984

Automated neuron tracing using the Marr-Hildreth zerocrossing technique.

Semiautomatic systems designed to trace neurons in three dimensions are slow and require many hours of work on the part of a human operator to trace even a single neuron completely. Attempts at constructing fully automatic systems have met with only limited success because of the dual problems of slow speed of travel down a fiber and time/space limitations on the intelligence of the program guiding the decision making. A novel approach to automatic tracing has been designed and initial implementation experiments have been carried out. Consideration of the five theoretical issues of edge detection, decision making, accuracy, robustness, and speed has led to the use of the Marr- Hildreth preprocessing filter and to a simple fiber-following algorithm that directly utilizes the output of that filter. Experimental results are encouraging and suggest that the approach is worthy of continued research.

Animals↗
PubMedDate not supplied

Computer-assisted dynamic integration of multiple medical thesauruses.

We have previously described a user-interactive rule-based computer program (Dyna-SaurI) designed for dynamic thesaurus integration, and demonstrated its efficacy on integrating dermatological subsets of the MeSH and SNOMED thesauruses. In the present study, we have refined our rules for merging and mapping multiple thesauruses and tested these rules. We then applied them with a set of optimized parameters to the integration of a third thesaurus, a subset of the International Coding Index for Dermatology, with the Integrated MeSH-SNOMED thesaurus. The parameter changes resulted in improved ranking of more specific and conceptually closer terms.

Abstracting and Indexing↗
PubMed1994

Use of open standards to implement health maintenance guidelines in a clinical workstation.

We are developing a clinical workstation which integrates access to health maintenance guidelines with access to a computer-based medical record. In order to enhance the portability of such a system, we emphasize the use of open standards which can be used in diverse clinical environments. We discuss the use of relational database and expert system technology to provide both patient-specific and patient-independent access to clinical guidelines. We use the Arden Syntax as the format for a textual library which facilitates the storage of structured medical knowledge.

Artificial Intelligence↗
PubMed1992

The effect of noise and biases on the performance of machine learning algorithms.

This paper describes the results of experiments with a machine learning algorithm for the induction of classification trees. We mainly address the impact of noise on the resulting classification tree and on the classification results obtained with the derived tree. We use the domain of the biochemical assessment of thyroid diseases as an example. Some suggestions for quality assessment are outlined that should be available in tools that assist users in deriving classification trees in noisy domains.

Algorithms↗
PubMed1987

Episodic, semantic and procedural memory in a case of amnesia at an early age.

The patient C.C. developed an amnesic syndrome at the age of 10 yr. Like adult amnesics, C.C. demonstrated impaired episodic memory for both verbal and visual materials although immediate memory span was spared. However, striking deficits were also observed on a wide variety of semantic memory tasks, including reading vocabulary and verbal fluency tests, semantic classification and lexical decision tasks and tests of verbal intelligence. On the other hand, C.C. showed normal learning and retention of two procedural tasks. It was argued that this evidence is inconsistent with the view that the amnesic syndrome represents a selective defect of episodic memory that leaves semantic memory relatively unaffected.

Amnesia↗
PubMed1994

EPISTOL: the future of knowledge based systems and techniques for the health sector.

This paper reports on EPISTOL, a project set up to provide a perspective on how knowledge based systems are going to be used in the health sector 5-10 years from now, and how should this expected use influence the planning of research and development work up to that period. The results of the project are aimed to aid the planning of future programmes concerned with research and development in health telematics, namely the fourth Framework Programme of the Commission of the European Communities.

Artificial Intelligence↗
PubMed1994

Qualitative Reasoning methods for CELSS modeling.

Qualitative Reasoning (QR) is a branch of Artificial Intelligence that arose from research on engineering problem solving. This paper describes the major QR methods and techniques, which, we believe, are capable of addressing some of the problems that are emphasized in the literature and posed by CELSS modeling, simulation, and control at the supervisory level.

Artificial Intelligence↗
PubMedDate not supplied

Approaching the millennium: perinatal problems and software solutions.

Strategic planning for rational development of perinatal computing capabilities for the year 2000 should be driven by anticipated trends in (1) the health care business, (2) computer technology and (3) medicine, as well as (4) the needs of perinatal practitioners. In the USA, health care is the fastest growing segment of the economy. This will produce increasing attention from hardware and software developers, and vendors, and will lead to a proliferation of computing platforms, operating systems and specific medical application software. Desktop computers, already capable of 20 million instructions per second (MIPS) with massive storage capacities, will continue to evolve and fall in price. Increasingly, perinatologists will develop software packages to facilitate patient care in their own environments. All of these trends will lead to severe fragmentation in medical computing. Simultaneously, however, the need for integrated institutional computer-based data access for quality assurance and fiscal and operations management will increase. Perinatal care will be more regionalized, complex and rigorous with new clinical trial- and effectiveness research-based interventions, as well as molecular diagnosis and therapy. To practice appropriately, clinicians will need to be familiar with computer capabilities. Having been exposed to computer-aided instruction (CAI) at the undergraduate and postgraduate levels, they will except on-line access to detailed and accurate patient information with linkage to laboratory, radiology and other medical databases, as well as to reference databases, such as Medlines and the Oxford Database of Perinatal Trials. Artificial intelligence (AI) software may support perinatal decision making; computerized professional and facility billing will be available.

Forecasting↗
PubMed1993

The representation of medical reasoning models in resolution-based theorem provers.

First-order predicate logic essentially is a language to express knowledge concerning objects and relationships between objects in a domain. Many medical problems can be cast naturally in such terms. In this paper the suitability of logic as a knowledge-representation formalism for building medical expert systems is investigated. In particular, we investigate the logical representation of three typical reasoning models in medicine: diagnostic, anatomical and causal reasoning. It turns out that each of these models has its own characteristic logical structure. Furthermore, the pragmatics of using theorem-proving techniques in consulting such logic-based medical expert systems is discussed. In particular, attention is paid to the use of a meta-level architecture to improve the applicability of theorem-proving techniques in building expert systems.

Anatomy↗
PubMed1995

Situated clinical cognition.

The features characterizing study of clinical cognition in situ are formulated as: Re-cognition of context, culture, history and affect. Socializing and phenomenalistic elements are again included in the research agenda. Interest for representations: an analysis level is reserved for the symbols, rules and images relevant to define in models of clinical cognition. De-emphasis on computer modeling: investigations focus on the 'functional systems' in which computers are involved. Rootedness in classical philosophical problems: issues concerning situated clinical cognition are connected to the width of available theoretical literature. Belief in interdisciplinary studies: productive interactions between the new and traditional disciplines is anticipated, implying that new shared methods have to be developed. When scientific perspectives are broadened, a new balance has to be found between the relevance of the subject of study and methodological rigor. The situated clinical cognition framework is to allow for moving between models, theories, and perspectives, as it does not presuppose a singular model of clinical thinking.

Artificial Intelligence↗
PubMed2004

A comparison of learning algorithms for Bayesian networks: a case study based on data from an emergency medical service.

Due to the uncertainty of many of the factors that influence the performance of an emergency medical service, we propose using Bayesian networks to model this kind of system. We use different algorithms for learning Bayesian networks in order to build several models, from the hospital manager's point of view, and apply them to the specific case of the emergency service of a Spanish hospital. This first study of a real problem includes preliminary data processing, the experiments carried out, the comparison of the algorithms from different perspectives, and some potential uses of Bayesian networks for management problems in the health service.

Algorithms↗
PubMed2005

An intelligent system for automatic detection of gastrointestinal adenomas in video endoscopy.

Today 95% of all gastrointestinal carcinomas are believed to arise from adenomas. The early detection of adenomas could prevent their evolution to cancer. A novel system for the support of the detection of adenomas in gastrointestinal video endoscopy is presented. Unlike other systems, it accepts standard low-resolution video input thus requiring less computational resources and facilitating both portability and the potential to be used in telemedicine applications. It combines intelligent processing techniques of SVMs and color-texture analysis methodologies into a sound pattern recognition framework. Concerning the system's accuracy this was measured using ROC analysis and found to exceed 94%.

Adenoma↗
PubMed2005

Flexible information storage in MUDR(II) EHR.

An important research task of the EuroMISE Centre is the applied research in the field of electronic health record (EHR) design including electronic medical guidelines and intelligent systems for data mining and decision support. The research in this field was inspired by several European projects. We have proposed a mathematical meta-description of a flexible information storage model based on the experience gathered in cooperation in those projects. In this model, we use two basic structures called a knowledge base and data files. We describe those two structures using the graph theory concepts. Furthermore, we use logical formulas to express conditions that should be valid. Additionally, we present a description of a global system architecture of a 3-tier EHR application with interfaces based on the latest technologies; predominately on Web Services, SOAP, XML, HTTP, CORBA, etc. According to our experience and test results gained from the MUDR EHR usage, we describe an open universal solution, which can be applied as the EHR kernel of hospital information systems. To realize this approach in a daily practice for health professionals we have started a co-operative project with clinical information systems developers. Within that project we are developing a new system for continual shared health care.

Biomedical Research↗
PubMed2004

Incorporating ideas from computer-supported cooperative work.

Many information systems have failed when deployed into complex health-care settings. We believe that one cause of these failures is the difficulty in systematically accounting for the collaborative and exception-filled nature of medical work. In this methodological review paper, we highlight research from the field of computer-supported cooperative work (CSCW) that could help biomedical informaticists recognize and design around the kinds of challenges that lead to unanticipated breakdowns and eventual abandonment of their systems. The field of CSCW studies how people collaborate with each other and the role that technology plays in this collaboration for a wide variety of organizational settings. Thus, biomedical informaticists could benefit from the lessons learned by CSCW researchers. In this paper, we provide a focused review of CSCW methods and ideas-we review aspects of the field that could be applied to improve the design and deployment of medical information systems. To make our discussion concrete, we use electronic medical record systems as an example medical information system, and present three specific principles from CSCW: accounting for incentive structures, understanding workflow, and incorporating awareness.

Artificial Intelligence↗
PubMed2005

A user-centered framework for redesigning health care interfaces.

Numerous health care systems are designed without consideration of user-centered design guidelines. Consequently, systems are created ad hoc, users are dissatisfied and often systems are abandoned. This is not only a waste of human resources, but economic resources as well. In order to salvage such systems, we have combined different methods from the area of computer science, cognitive science, psychology, and human-computer interaction to formulate a framework for guiding the redesign process. The paper provides a review of the different methods involved in this process and presents a life cycle of our redesign approach. Following the description of the methods, we present a case study, which shows a successfully applied example of the use of this framework. A comparison between the original and redesigned interfaces showed improvements in system usefulness, information quality, and interface quality.

Artificial Intelligence↗