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At least 523 records · Page 29Linked to original sources
PubMed2005

Pathways to evidence-based knowledge in orthopaedic surgery: an international survey of AO course participants.

The aim of this study was to gain information about how orthopaedic surgeons use evidence-based literature and how this is influenced by their knowledge of evidence-based medicine. We administered a questionnaire to participants at courses of the Association for the Study of Internal Fixation (AO-ASIF) in Davos, Switzerland, in December 2003. Special attention was paid to the surgeons' educational level, affiliations, and the infrastructure and evidence sources they used. In addition, we tested participants on their knowledge and attitude to evidence-based orthopaedic surgery (EBOS). Of 1,274 course participants, 456 completed the questionnaire. Of 446 respondents, 300 had heard of EBOS, but only 45% could define it correctly. Nearly two thirds identified scientific publications as their main source of scientific knowledge. The respondents' attitudes to and awareness of EBOS principles was high, but it did not influence their manner of searching for scientific information or their trust in various sources of recommendations.

Adult↗
PubMed2006

Using evidence-based knowledge in a nursing documentation system.

Just as Florence Nightingale based her care delivery decisions on the analysis of outcome results, clinical information systems can support evidence-based nursing content and analysis tools to promote the practice of knowledge-driven nursing. This system demonstration will depict how nursing evidence is embedded into an automated assessment and documentation process to achieve immediate results in such areas as:* Compliance with core quality and clinical performance metrics--including skin integrity, nutritional deficits, IV site care and falls risks. * Integration of patient safety measures such as allergy documentation and medication reconciliation. * Reminders about care management initiatives such as completion of advanced directives and promotion of preventive health measures.

Documentation↗
PubMed1990

Knowledge-based computer systems for radiotherapy planning.

Radiation therapy is one of the first areas of clinical medicine to utilize computers in support of routine clinical decision making. The role of the computer has evolved from simple dose calculations to elaborate interactive graphic three-dimensional simulations. These simulations can combine external irradiation from megavoltage photons, electrons, and particle beams with interstitial and intracavitary sources. With the flexibility and power of modern radiotherapy equipment and the ability of computer programs that simulate anything the machinery can do, we now face a challenge to utilize this capability to design more effective radiation treatments. How can we manage the increased complexity of sophisticated treatment planning? A promising approach will be to use artificial intelligence techniques to systematize our present knowledge about design of treatment plans, and to provide a framework for developing new treatment strategies. Far from replacing the physician, physicist, or dosimetrist, artificial intelligence-based software tools can assist the treatment planning team in producing more powerful and effective treatment plans. Research in progress using knowledge-based (AI) programming in treatment planning already has indicated the usefulness of such concepts as rule-based reasoning, hierarchical organization of knowledge, and reasoning from prototypes. Problems to be solved include how to handle continuously varying parameters and how to evaluate plans in order to direct improvements.

Artificial Intelligence↗
PubMed2006

Knowledge-based design of target-focused libraries using protein-ligand interaction constraints.

Here we present a new strategy for designing and filtering potentially massive combinatorial libraries using structural information of a binding site. We have developed a variation of the structural interaction fingerprint (SIFt) named r-SIFt, which incorporates the binding interactions of variable fragments in a combinatorial library. This method takes into account the 3D structure of the active site of the target molecule and translates desirable ligand-target binding interactions into library filtering constraints. We show using the MAP kinase p38 as a test case that we can efficiently analyze and classify compounds on the basis of their abilities to interact with the target in the desired binding mode. On the basis of these classifications, decision tree models were generated using the molecular descriptors of the compounds as predictor variables. Our results suggest that r-SIFt coupled with the classification models should be a valuable tool for structure-based focusing of combinatorial chemical libraries.

Binding Sites↗
PubMed2001

[Progress in knowledge-based X-ray fluorescence spectrometry].

The review focuses on the expert systems and knowledge engineering in X-ray fluorescence spectrometry. It includes mainly a knowledge-controlled strategy combining the scan-based method with the fixed channel measurements, a XRF interpretation system of spectra with fuzzy logic and pattern recognition, and an expert system for qualitative interpretation of XRF spectra using a certainty factor. In the review, a series of the studies of exploring the knowledge engineering system in XRF are also included, which consists of four parts, i.e. spectra identification, pattern recognition with decision-making, quantitative determination combined with the theoretical alpha coefficients and neural networks, and XRF analysis without standards.

Algorithms↗
PubMed1989

Knowledge-based design of artificial worlds.

We review the concepts of knowledge representation and modelling and simulation methodology which facilitate computer exploration of alternative artificial worlds, such as self-sufficient human habitats. An object-oriented computer environment which supports such simulation studies is briefly described. A simplified example of an artificial world model is given to demonstrate the power of the approach.

Artificial Intelligence↗
PubMed2006

TimeTree: a public knowledge-base of divergence times among organisms.

UNLABELLED: Biologists and other scientists routinely need to know times of divergence between species and to construct phylogenies calibrated to time (timetrees). Published studies reporting time estimates from molecular data have been increasing rapidly, but the data have been largely inaccessible to the greater community of scientists because of their complexity. TimeTree brings these data together in a consistent format and uses a hierarchical structure, corresponding to the tree of life, to maximize their utility. Results are presented and summarized, allowing users to quickly determine the range and robustness of time estimates and the degree of consensus from the published literature. AVAILABILITY: TimeTree is available at http://www.timetree.net

Biological Evolution↗
PubMed2003

BioMeKe: an ontology-based biomedical knowledge extraction system devoted to transcriptome analysis.

Semantic interoperability between knowledge bases in medicine, and knowledge base in genomics and molecular biology will lead to advances in fundamental research as well as to improved patient care. DNA chips strategy is used for transcriptome analysis in order to identify deregulated genes in physio-pathological conditions. The objective of the BioMedical Knowledge Extraction project (BioMeKe) is to develop a knowledge warehouse in the context of transcriptome analysis during liver diseases. Knowledge sources include ontologies, related terminologies and annotations linked towards public databases (e.g., SWISSPROT). BioMeKe has been developed to have access to information using systematic investigation upon a concept, gene, gene products, pathology, or any target keyword, and is based on the combination of several relevant resources: UMLS, GeneOntology, MeSH supplementary terms, GOA, and HUGO. Current efforts are focusing on exploiting this ontology-based Knowledge Extractor, to enrich the expression data on genes delivered by a liver specific DNA microarray for better assistance of analysis.

Databases, Genetic↗
PubMed1992

An object oriented approach to interpret medical knowledge based on the Arden syntax.

A method is presented where medical knowledge modules, written in the Arden Syntax, are used in a decision-support system (DSS). Knowledge modules are, after syntax-checking, translated into the object oriented programming language C++, compiled and linked to the DSS. The object oriented approach together with developed tools, such as knowledge editor and translator, makes it possible to implement the Arden Syntax and to get an efficient, easy-maintained DSS. Work on a prototype shows that this approach has several advantages when building a DSS where medical knowledge is represented in the Arden Syntax.

Artificial Intelligence↗
PubMed2006

Methodological issues for the information model of a knowledge-based telehealthcare system for nephrology (Nefrotel).

Several studies point out the paradox that classic telemedicine by which doctor interacts remotely with patients in real-time is disappearing despite it has not been widely adopted yet. Many cues indicate that health information technologies will be finally adopted because of the growth in health expenditure and the emerging healthcare challenges. Notwithstanding, a detailed analysis of the referred concern has led us to propose a shift in the paradigm of telemedicine systems. This paper presents the major methodological issues of the information model of a novel telehealthcare system for nephrology (Nefrotel) which supports the cited shift in the paradigm. With this objective, we first revise the technological requirements of the database of Nefrotel, and second analyze the current scenario of health information model standards. Our study has shown that it is possible to ensure the compliance and evolution of Nefrotel with information model standards, maximizing its interoperability.

Computer Communication Networks↗
PubMed2007

Computational basis of knowledge-based conformational probabilities derived from local- and long-range interactions in proteins.

The probabilities of the various basins in Ramachandran maps are examined critically. The theoretical basis of probability calculations both from molecular computations and from protein libraries are discussed. The well-defined basins of the Ramachandran maps are treated as rotational isomeric states. Statistical independence and dependence of the states of different residues along the peptide chain are discussed. The Flory isolated pair hypothesis, near neighbor correlations, context effects, and long-range correlations are examined critically. A method of evaluating long-range correlations in helical and extended sequences is introduced in analogy with earlier polymer theory. Three different protein libraries are constructed where data is considered from residues in the (i) coiled regions, (ii) all regions, and (iii) only the helical and extended regions of proteins. Singlet and pairwise dependent probabilities calculated from these libraries are used to predict whether a given sequence is helical or extended. Predictions using pairwise dependence were not better than those using singlet probabilities. Modeling of long-range correlations improved the predictions significantly. Removal of the Chameleon sequences from the data set also improved the predictions, but to a lesser extent.

Amino Acid Sequence↗