SEARCH · PubMed Health

Results for “Knowledge base”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20Linked to original sources

PubMed1998

Postgraduate education: does it improve the knowledge base of practitioners with time?

PURPOSE: We evaluate the effect of the provision of postgraduate educational material on improving practitioner knowledge base during a 3-year period. MATERIALS AND METHODS: A total of 210 urologists were provided 67 monographs in a 2-year period. They were given a pretest before and posttest 1 year after receipt of all monographs. RESULTS: There was significant improvement in posttest scores for the group as a whole. Improvement correlated with years post-training and number of monographs read. Multivariate analysis revealed the number of monographs read was the only independent predictor of outcome. CONCLUSIONS: Although the improvement in test scores was significant and did correlate with the postgraduate educational material read, it was modest. This finding raises significant concerns about the usefulness of this format for graduate medical education.

Clinical Competence↗

PubMed2000

Sequence-structure specificity of a knowledge based energy function at the secondary structure level.

MOTIVATION: This paper investigates the sequence-structure specificity of a representative knowledge based energy function by applying it to threading at the level of secondary structures of proteins. Assessing the strengths and weaknesses of an energy function at this fundamental level provides more detailed and insightful information than at the tertiary structure level and the results obtained can be useful in tertiary level threading. RESULTS: We threaded each of the 293 non-redundant proteins onto the secondary structures contained in its respective native protein (host template). We also used 68 pairs of proteins with similar folds and low sequence identity. For each pair, we threaded the sequence of one protein onto the secondary structures of the other protein. The discerning power of the total energy function and its one-body, pairwise, and mutation components is studied. We then applied our energy function to a recent study which demonstrated how a designed 11-amino acid sequence can replace distinct segments (one segment is an alpha-helix, the other is a beta-sheet) of a protein without changing its fold. We conducted random mutations of the designed sequence to determine the patterns for favorable mutations. We also studied the sequence-structure specificity at the boundaries of a secondary structure. Finally, we demonstrated how to speed up tertiary level threading by filtering out alignments found to be energetically unfavorable during the secondary structure threading. AVAILABILITY: The program is available on request from the authors. CONTACT: xud@ornl.gov

Amino Acid Sequence↗

PubMed2000

Validation of ICTERUS, a knowledge-based expert system for Jaundice diagnosis.

The study aimed to describe an example of the assessment and validation of knowledge-based clinical expert systems. The paper focuses on ICTERUS, an expert system for jaundice diagnosis. It describes system design, the methodology applied for upgrading and validating the program, and the most important outcomes of the validation procedure. The clinical validation of the system on a very large European database (Euricterus Project) shows that diagnostic conclusions are reliable in about 70% of eligible cases. This figure appears acceptable for a system which provides decision support only on the basis of clinical data, assuming that the final decision is achieved under user responsibility. Expected biases, limitations and inconsistencies in the practical application of the system are discussed.

Analysis of Variance↗

PubMed1996

Validation of a knowledge-based boundary detection algorithm: a multicenter study.

A completely operator-independent boundary detection algorithm for multigated blood pool (MGBP) studies has been evaluated at four medical centers. The knowledge-based boundary detector (KBBD) algorithm is nondeterministic, utilizing a priori domain knowledge in the form of rule sets for the localization of cardiac chambers and image features, providing a case-by-case method for the identification and boundary definition of the left ventricle (LV). The nondeterministic algorithm employs multiple processing pathways, where KBBD rules have been designed for conventional (CONV) imaging geometries (nominal 45 degrees LAO, nonzoom) as well as for highly zoomed and/or caudally tilted (ZOOM) studies. The resultant ejection fractions (LVEF) from the KBBD program have been compared with the standard LVEF calculations in 253 total cases in four institutions, 157 utilizing CONV geometry and 96 utilizing ZOOM geometries. The criteria for success was a KBBD boundary adequately defined over the LV as judged by an experienced observer, and the correlation of KBBD LVEFs to the standard calculation of LVEFs for the institution. The overall success rate for all institutions combined was 99.2%, with an overall correlation coefficient of r=0.95 (P<0.001). The individual success rates and EF correlations (r), for CONV and ZOOM geometers were: 98%, r=0.93 (CONV) and 100%, r=0.95 (ZOOM). The KBBD algorithm can be adapted to varying clinical situations, employing automatic processing using artificial intelligence, with performance close to that of a human operator.

Algorithms↗

PubMed1997

Novel knowledge-based mean force potential at atomic level.

We present a new approach at the atomic level for the development of knowledge-based mean force potentials (MFPs) that can be used in fold recognition, ab initio structure prediction, comparative modelling and molecular recognition. Our method is based on atom-type definitions, raising the total frequency of the pairwise distributions and leading to very accurate and specific distance-dependent energy functions. Forty different heavy atom types were defined depending on their bond connectivity, chemical nature and location level (side-chain or backbone). Using this approach it has been possible to obtain average frequencies of pairwise contacts about 15 times higher than the ones obtained using the classic way of one heavy atom definition for each amino acid (i.e. alpha-carbon, beta-carbon, virtual centroid or virtual beta-carbon co-ordinates). In this paper we use this approach to develop a MFP that can be used in fold recognition and we compare it with a classic MFP at the amino acid level compiled from the alpha-carbon distances between the different amino acid pairs. Both potentials involve all the pairwise contacts extracted from a non-redundant folds database of 180 protein chains with a sequence identity threshold of 25%. The pairwise energy functions of the MFP at the atomic level have a deep and very well defined minimum for each pairwise interaction, in contrast to the same curves obtained from the MFP developed at the amino acid level, which generally have multiple minima with similar depth. Our results also show that this MFP is able to produce very similar energy profiles for couples of proteins that share a very low sequence identity but are closely related at the structural level. When these profiles are plotted considering the structure-structure alignment, they are mostly superimposed, showing a correlation with the structure-structure similarity. In the same test, the MFP at the amino acid level fails to produce similar profiles. We suggest that using this MFP at the atomic level in the last stages of fold recognition or threading, when some candidates are available, can improve the sequence-structure alignments and, therefore, the final models. We also discuss the possibility of using this approach in the development of new MFPs to be used in ab initio structure prediction, comparative modelling and molecular recognition procedures.

Amino Acids↗

PubMedDate not supplied

[Artificial intelligence--the knowledge base applied to nephrology].

The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

Artificial Intelligence↗

PubMed2005

Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management.

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.

Algorithms↗

PubMed1995

Knowledge-based temporal abstraction in diabetes therapy.

We suggest a general framework for solving the task of creating abstract, interval-based concepts from time-stamped clinical data. We refer to this problem-solving framework as the knowledge-based temporal-abstraction (KBTA) method. The KBTA method emphasizes explicit representation, acquisition, maintenance, reuse, and the sharing of knowledge required for abstraction of time-oriented clinical data. We describe the subtasks into which the KBTA method decomposes its task, the problem-solving mechanisms that solve these subtasks, and the knowledge necessary for instantiating these mechanisms in a particular clinical domain. We have implemented the KBTA method in the RESUME system and have applied it to the task of monitoring the care of insulin-dependent diabetics.

Artificial Intelligence↗

PubMed1988

The AI/RHEUM knowledge-based computer consultant system in rheumatology. Performance in the diagnosis of 59 connective tissue disease patients from Japan.

AI/RHEUM is a knowledge-based computer consultant system for the diagnosis of rheumatic diseases. Its diagnostic accuracy was evaluated using information that was supplied by Japanese rheumatologists on 59 patients with connective tissue diseases. The diagnoses of the AI/RHEUM model were in full or partial agreement with those of the Japanese rheumatologists in 54 of 59 cases (92%). Preliminary evaluation of the criteria tissue disease showed a sensitivity of 90% and a specificity of 96%.

Artificial Intelligence↗

PubMed2004

Annotation of post-translational modifications in the Swiss-Prot knowledge base.

High-throughput proteomic studies produce a wealth of new information regarding post-translational modifications (PTMs). The Swiss-Prot knowledge base is faced with the challenge of including this information in a consistent and structured way, in order to facilitate easy retrieval and promote understanding by biologist expert users as well as computer programs. We are therefore standardizing the annotation of PTM features represented in Swiss-Prot. Indeed, a controlled vocabulary has been associated with every described PTM. In this paper, we present the major update of the feature annotation, and, by showing a few examples, explain how the annotation is implemented and what it means. Mod-Prot, a future companion database of Swiss-Prot, devoted to the biological aspects of PTMs (i.e., general description of the process, identity of the modification enzyme(s), taxonomic range, mass modification) is briefly described. Finally we encourage once again the scientific community (i.e., both individual researchers and database maintainers) to interact with us, so that we can continuously enhance the quality and swiftness of our services.

Computational Biology↗

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↗

PubMed2001

A knowledge-based multimedia telecare system to improve the provision of formal and informal care for the elderly and disabled.

We have developed a knowledge-based multimedia telecare system, based on a multimedia PC connected by ISDN at 128 kbit/s. The user display is a television. Multimedia material is accessed through a browser-based interface. A remote-control handset is used as the main means of interaction, to ensure ease of use and overcome any initial reservations resulting from 'technophobia' on the part of the informal carer. The system was used in 13 family homes and four professional sites in Northern Ireland. The evaluations produced positive comments from the informal carers. There are plans to expand the use of the system.

Aged↗

PubMedDate not supplied

Evaluation stages and design steps for knowledge-based systems in medicine.

After the early experiments in artificial intelligence a methodology is emerging around advanced systems for the management of medical knowledge. The stress is moving away from the implementation of prototypes to the evaluation. It is possible to adapt and to apply this to field evaluation techniques already developed in similar contexts of knowledge management (books, drugs, epidemiology, consultants, etc.). The time is ready for a further step: to envisage a methodology for the design of real systems that cope with the 'knowledge environment' of the user. Every stage of the evaluation process is re-examined here, and considered as a framework to define goals and criteria about a step of design: (1) the impact of the system on the progress of health care provision (priorities, cost-benefit analysis, share of tasks among different media); (2) effectiveness in the end-user's environment and long-term effects on his behaviour (changes in people's role and responsibilities, improvements in the quality of data, acceptance of the system); (3) the intrinsic efficiency of the system apart from the operational context (correctness of the knowledge base, appropriateness of the reasoning). The need to differentiate the test sample into three classes (obvious, typical, atypical) is emphasized, discussing the influence on both evaluation and design. In particular the difficulty of having 'gold standards' on atypical cases, due to the disagreement among the experts, leads to the definition of two alternative attitudes: the 'standardization mode' and the 'brain-storming mode'.

Expert Systems↗

PubMed2002

Automated assignment of NOESY NMR spectra using a knowledge based method (KNOWNOE).

Automated assignment of NOESY spectra is a prerequisite for automated structure determination of biological macromolecules. With the program KNOWNOE we present a novel, knowledge based approach to this problem. KNOWNOE is devised to work directly with the experimental spectra without interference of an expert. Besides making use of routines already implemented in AUREMOL, it contains as a central part a knowledge driven Bayesian algorithm for solving ambiguities in the NOE assignments. These ambiguities mainly arise from chemical shift degeneration which allows multiple assignments of cross peaks. Using a set of 326 protein NMR structures, statistical tables in the form of atom-pairwise volume probability distributions (VPDs) were derived. VPDs for all assignment possibilities relevant to the assignments of interproton NOEs were calculated. With these data for a given cross peak with N possible assignments Ai (i = 1,...,N) the conditional probabilities P(Ai, a/V0) can be calculated that the assignment Ai determines essentially all (a-times) of the cross peak volume V0. An assignment Ak with a probability P(Ak, a/V0) higher than 0.8 is transiently considered as unambiguously assigned. With a list of unambiguously assigned peaks a set of structures is calculated. These structures are used as input for a next cycle of iteration where a distance threshold Dmax is dynamically reduced. The program KNOWNOE was tested on NOESY spectra of a medium size protein, the cold shock protein (TmCsp) from Thermotoga maritima. The results show that a high quality structure of this protein can be obtained by automated assignment of NOESY spectra which is at least as good as the structure obtained from manual data evaluation.

Algorithms↗

PubMed2004

Improving information prescription to parents of premature infants through an OWL-based knowledge mediator.

In the Baby CareLink system, information prescription plays an important role in preparing parents of premature infants for the eventual discharge to home of their children. However, the prescription process requires scarce clinician time in order to dispense information, and can become cumbersome as content bases grow in size. We describe the development of an OWL-based knowledge mediator to facilitate information prescription. We describe 1) the initial development of a clinical vocabulary for neonatology using OWL-DL; 2) the reuse of the vocabulary to represent prototypical premature infants and their typical clinical problems and treatments; 3) the software components used to integrate terminology and inferencing services with Baby CareLink. We demonstrate multifaceted uses for description logics in a clinical application, reuse of a base vocabulary for domain knowledge representation, and use of the OWL language in representing clinical vocabularies. We believe that semi-automated knowledge mediation will enhance the process of electronic information prescription using large clinical content collections.

Education↗

PubMed1996

Database and knowledge base integration in decision support systems.

Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases.

Artificial Intelligence↗

PubMed2001

Scientific vs. clinical-based knowledge in psychology: a concealed moral conflict.

Psychology and the other mental health professions are bitterly divided between the proponents of scientific vs. clinical-based knowledge. Though these two groups agree on little related to assessment, treatment or outcome evaluation, they share a belief in the moral neutrality of the knowledge they do possess. It is argued here that this moral neutrality is a myth, and that it is exactly the unacknowledged and incompatible moral positions inherent in clinical and research practices that are at the center of this controversy. The nature of moral problems, the fundamental moral value positions prevalent in our culture, and the specific moral values associated with each side of this schism are explored. While these moral differences may not all be resolved by being recognized and discussed, the process of dialogue can not but help us bridge the current chasm. To this end it is recommended that psychologists and other mental health professionals adopt a "truth-in-moral-packaging" rule that requires both clinicians and scientific researchers to define openly and clearly the moral objectives that infuse their work.

Attitude↗

PubMedDate not supplied

A feature dictionary supporting a multi-domain medical knowledge base.

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Artificial Intelligence↗