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Results for “Knowledge base”

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PubMed1994

ESTEEM (European Standardised Telematic Tool to Evaluate EMG Knowledge-Based Systems and Methods): AIM Project A2010.

ESTEEM is an AIM project which is primarily concerned with how to develop, integrate and clinically test knowledge-based systems for electromyography (EMG) in order to get them generally acceptable, useful and applicable into disseminated clinical routines. A medical workstation entitled the 'EMG-Platform' on which different kinds of application modules including KBSs can be interfaced to a kernel is being developed. Accordingly, an EMG communication protocol is being developed. The ESTEEM consortium is composed of a technical specialist group and a group of clinical experts in EMG from seven European countries. The last group has, besides extensive data collection for building up a multicentre EMG database, agreed on a common EMG terminology and a subsequent general EMG data set specification which covers the informatic needs for describing an EMG examination of different 'EMG schools'.

Electromyography↗

PubMed2003

Knowledge-based approach to septic shock patient data using a neural network with trapezoidal activation functions.

In this contribution we present an application of a knowledge-based neural network technique in the domain of medical research. We consider the crucial problem of intensive care patients developing a septic shock during their stay at the intensive care unit. Septic shock is of prime importance in intensive care medicine due to its high mortality rate. Our analysis of the patient data is embedded in a medical data analysis cycle, including preprocessing, classification, rule generation and interpretation. For classification and rule generation we chose an improved architecture based on a growing trapezoidal basis function network for our metric variables. Our results extend those of a black box classification and give a deeper insight in our patient data. We evaluate our results with classification and rule performance measures. For feature selection we introduce a new importance measure.

Abdomen↗

PubMed1996

Knowledge-based systems, artificial neural networks and pattern recognition: applications to biotechnological processes.

Recent years have witnessed the increasing application of artificial intelligence techniques, specifically, knowledge-based systems, artificial neural networks, and pattern recognition, to biotechnological processes. Although progress has been made in simple control applications, more work is needed to establish the advantages of these techniques for industrial process control, for diagnosis/monitoring, and to upgrade the information content of historical data.

Biotechnology↗

PubMedDate not supplied

Knowledge-based prediction of protein structures and the design of novel molecules.

Prediction of the tertiary structures of proteins may be carried out using a knowledge-based approach. This depends on identification of analogies in secondary structures, motifs, domains or ligand interactions between a protein to be modelled and those of known three-dimensional structures. Such techniques are of value in prediction of receptor structures to aid the design of drugs, herbicides or pesticides, antigens in vaccine design, and novel molecules in protein engineering.

Amino Acid Sequence↗

PubMedDate not supplied

Technical aspects of internet-based knowledge presentation in radiotherapy.

Three-dimensional radiotherapy planning is a complex and time-consuming optimization process which requires much experience. To simplify and to speed up the process of treatment planning as well as to exchange experience and therapeutic knowledge, the department of Medical Physics at the German Cancer Research Centre (DKFZ) in Heidelberg is developing an Internet-based 3D Radiotherapy planning and Information System (IRIS). IRIS designed internet-based client-server application, implemented using Java, CORBA and PVM. The concept of IRIS combines the functionality of an interactive tutorial with a discussion forum, teleconferencing tool and an atlas of dose distributions. Furthermore an integral knowledge-based system provides automatically generated, preoptimized treatment plans. This paper explains the technical design of the system and gives an overview of experiences gained by the technical realization of a first prototype using currently available internet technology. The prototype is currently running for testing in the intranet of DKFZ.

Artificial Intelligence↗

PubMed2001

What is a necessary knowledge base for sleep professionals?

Sleep medicine is multidisciplinary, and sleep medicine professionals should be trained to evaluate and treat all 88 sleep disorders. Sleep medicine specialists require a fund of knowledge that goes beyond what is obtained during a pulmonary fellowship. Skills required for a pulmonary sleep professional include: sleep medicine, neurobiology, psychiatry, neuro-psychology, neurology, pediatrics, and even limited exposure in otolaryngology, oral maxillofacial surgery, and dentistry. There is a paucity of published information concerning curricular requirements. Required skills for a sleep professional include proficiency in the clinical skills of sleep medicine as well as the technical skills of polysomnography. There is a very large knowledge content area requirement in both the basic sciences of sleep and the clinical aspects of sleep medicine. There are also important clinical skills content areas. As with all medical professionals, sleep professionals should have the highest ethical standards and a strong sense of responsibility toward their patients. A sleep medicine professional also has to be knowledgeable about administrative and legal aspects specific to sleep medicine. This essay reviews a sleep professional knowledge base model with emphasis on the requirements for a pulmonary sleep professional.

Health Knowledge, Attitudes, Practice↗

PubMed2002

The helpful patient record system: problem oriented and knowledge based.

In contrast to existing computerized patient record systems, which merely offer static functionality for storage and presentation, a helpful patient record system is a problem-oriented, knowledge-based system which provides the clinician with situation-specific information from the patient record, relevant to the activity within the patient care process. We suggest extending the data model of current patient record systems with (1) knowledge for recognizing and interpreting care situations, (2) knowledge of how clinicians work and what information they need, and (3) means to rank information according to its relevance in a given situation. We present a framework that enables representation of three prerequisite features for a future helpful patient record system: the primary care workflow process, the problem-oriented information model, and means to identify relevant information to the care process and medical decisions.

Artificial Intelligence↗

PubMed1998

Knowledge-based visualization of time-oriented clinical data.

We describe a domain-independent framework (KNAVE) specific to the task of interpretation, summarization, visualization, explanation, and interactive exploration in a context-sensitive manner through time-oriented raw clinical data and the multiple levels of higher-level, interval-based concepts that can be abstracted from these data. The KNAVE exploration operators, which are independent of any particular clinical domain, access a knowledge base of temporal properties of measured data and interventions that is specific to the clinical domain. Thus, domain-specific knowledge underlies the domain-independent semantics of the interpretation, visualization, and exploration processes. Initial evaluation of the KNAVE prototype by a small number of users with variable clinical and informatics training has been encouraging.

Artificial Intelligence↗

PubMed1998

Why discourse structures in medical reports matter for the validity of automatically generated text knowledge bases.

The automatic analysis of medical full-texts currently suffers from neglecting text coherence phenomena such as reference relations between discourse units. This has unwarranted effects on the description adequacy of medical knowledge bases automatically generated from texts. The resulting representation bias can be characterized in terms of artificially fragmented, incomplete and invalid knowledge structures. We discuss three types of textual phenomena (pronominal and nominal anaphora, as well as textual ellipsis) and outline basic methodologies how to deal with them.

Artificial Intelligence↗

PubMed1990

Knowledge-based battery design of short-term tests based on dose information.

A construction of batteries of short-term tests (STTs) is described which is based on a classification of 73 chemicals in regard to their carcinogenicity. The 73 chemicals were studied within the U.S. National Toxicology Program (Ashby and Tennant, 1988). The batteries are validated using the classification of 35 additional chemicals. They are defined by logically structured combinations of rules. The single rules are defined by the z-scores of the logarithmic values of the limiting doses obtained from the 4 in vitro STTs used in the study by Ashby and Tennant. The limiting dose is defined as the lowest effective dose or the highest ineffective dose (Waters et al., 1987). The batteries are constructed by minimizing the number of disagreements with the classification by Ashby and Tennant. Compared with the results obtained from single STTs, 2 batteries of 3 STTs have higher concordances with the carcinogenicity data, namely 70% for the NTP data and 74-77% for the independent test data. In addition, a theoretical result shows that the proposed battery design, for a large enough learning set of chemicals, leads to results which are replicated with high probability on a large enough validation set. Based on the first results obtained with a limited number of chemicals it is concluded that the knowledge-based battery design is worth further development.

Animals↗

PubMed2003

Knowledge base evaluation of medicine residents on the gastroenterology service: Implications for competency assessments by faculty.

BACKGROUND AND AIMS: Clinician educators are asked to provide both formative and summative evaluations on the medical knowledge of residents. This study evaluated the accuracy of these evaluations and the perception of residents regarding the ability of faculty to assess medical knowledge. METHODS: Gastroenterology knowledge ratings provided by 15 faculty gastroenterologists on 49 internal medicine residents during a required gastroenterology rotation were correlated with performance on the gastroenterology subsection of the In-Training Examination for Internal Medicine. Residents also were surveyed regarding their perception of the ability of faculty to judge their knowledge of medical gastroenterology. RESULTS: The mean correlation (Kendall's tau b) of faculty ratings with performance on the ITE was 0.30 (P < 0.01). The range of correlation values for individual faculty (-0.39 to 0.80) indicated that some faculty were able to assess the medical knowledge of residents better than others. Residents, as well as the faculty themselves, perceived that faculty were able to rate their medical knowledge relatively well. CONCLUSIONS: The ability of faculty gastroenterologists to judge the knowledge of gastroenterology in their resident trainees was quite limited. Residents, as well as faculty, inaccurately perceive the ability of gastroenterologists to render professional judgments on their knowledge base as good. An end-of-rotation written examination would appear to be required to provide an accurate assessment of the medical knowledge of residents.

Adult↗

PubMed2004

Identification of compounds with nanomolar binding affinity for checkpoint kinase-1 using knowledge-based virtual screening.

A virtual screen of a subsection of the AstraZeneca compound collection was performed for checkpoint kinase-1 (Chk-1 kinase) using a knowledge-based strategy. This involved initial filtering of the compound collection by application of generic physical properties followed by removal of compounds with undesirable chemical functionality. Subsequently, a 3-D pharmacophore screen for compounds with kinase binding motifs was applied. A database of approximately 200K compounds remained for docking into the active site of Chk-1 kinase, using the FlexX-Pharm program. For each compound that docked successfully into the binding site, up to 100 poses were saved. These poses were then postfiltered using a customized consensus scoring scheme for a kinase, followed by visual inspection of a selection of the docked compounds. This resulted in 103 compounds being ordered for testing in the project assay, and 36 of these (corresponding to four chemical classes) were found to inhibit the enzyme in a dose-response fashion with IC(50) values ranging from 110 nM to 68 microM.

Amino Acid Motifs↗

PubMed1993

Object-oriented knowledge bases for the analysis of prokaryotic and eukaryotic genomes.

The amount of biological sequences introduced in the general collections, and the growing complexity of the biological knowledge require the construction of models to formalize this knowledge and particularly the relationships between several data types. Two examples of such situations are presented here, they result from the biological research lead in our team in the field of molecular evolution. ColiGene is a modelling of E. coli genetics devoted to the analysis of relationships between genomic sequences and gene expressivity. MultiMap implements a new formalization of genome maps allowing manipulation of "maps of maps" in two species. Application of ColiGene and MultiMap are not restricted to molecular evolution and, for instance, MultiMap offers new capabilities for infering data on a genome from knowledge on another species. This could be essential for many mapping projects (human, mouse but also other mammals like pig). Development and implementation of those models have been done using an object-oriented knowledge base management system (SHIRKA) interfaced with a dedicated genomic data base management system (ACNUC). Graphical interfaces have been designed to give an environment similar to the biological representations used by biologists.

Animals↗

PubMed1996

New directions for health: towards a knowledge base for public health action.

The need for new types of solutions to respond to community health needs, along with the poor fit between research and the knowledge needed for improving the health of populations, have stimulated a renewal process in the field of public health. Growing out of this movement, an international workshop held at the Nuffield Institute for Health, University of Leeds in 1993 took up issues related to the role and limitations of epidemiology as generally practiced today. Concern for creating a relevant and sound knowledge base for public health action was the impetus guiding this project. Some of the major topics taken up in the deliberations of the workshop are reflected in the selection of papers that follow. They are highlighted and supplemented with an overview of other issues taken up by the conferees in this introduction.

Artificial Intelligence↗

PubMed1999

Sustained performance of knowledge-based potentials in fold recognition.

We describe the results obtained using fold recognition techniques in our third participation in the CASP experiment. The approach relies on knowledge-based potentials for alignment production and fold identification. As indicated by the increase in alignment quality and fold identification reliability, the predictions improved from CASP1 to CASP3. In particular, we identified structural relationships in which no known evolutionary link exists. Our predictions are based on single sequences rather than multiple sequence alignments. Additionally, we voluntarily submitted only a single model for each target because, in our view, submission of a single model is the most stringent test. We describe the methods used, the strategy adopted in the predictions, and the prediction results and discuss future work.

Algorithms↗

PubMedDate not supplied

Structure-activity relationships for skin sensitization potential: development of structural alerts for use in knowledge-based toxicity prediction systems.

The development of qualitative structure-activity relationships for the prediction of skin sensitization potential, based on structural alerts (substructures associated with a toxicological mechanism), and suitable for incorporation as rules into a knowledge-based system is described. The structure dependence of the skin sensitization mechanism may be largely defined in terms of the presence or metabolic/nonmetabolic formation of protein reactive functional groups on the test compound and by the physicochemical requirements of significant skin penetration. The proposed structural alerts were tested on a data set of diverse chemicals. The results showed that the alerts have potential as preliminary indicators of skin sensitization potential for a wide range of low molecular weight chemicals.

Acylation↗

PubMed2002

Knowledge-based system for method development of chiral separations with capillary electrophoresis using highly-sulphated cyclodextrins.

Method development for chiral separations is not easy because it requires experience and many experimental possibilities can be chosen. In order to help the analyst, a knowledge-based system (KBS) for the rapid determination of experimental parameters, which allow a baseline separation of enantiomers, has been developed. On the basis of own laboratory knowledge, completed with literature data, rules were defined and a KBS was built. Five different techniques are considered in this KBS. This paper describes the capillary electrophoresis (CE) section, in which a strategy has been defined based on the use of highly-sulfated cyclodextrins as chiral selectors. A structured representation of the knowledge and its implementation in Toolbook software is presented.

Artificial Intelligence↗

PubMed1993

A knowledge-based approach to minimize baseline roll in chemical shift imaging.

A method has been developed to minimize baseline roll in chemical shift imaging (CSI). The technique is fully automated and employs knowledge based data processing in the frequency domain. The key feature of the algorithm is the computation of the "trough" and "ripple" components in the CSI data. The baseline roll can be regarded as an artifact that appears as a result of the summation of several sinc functions. Using prior knowledge, a mirror component corresponding to the artifact is created and added to the delayed spectrum. The method compensates for noise and zero-order phase error when computing the roll artifact. The results obtained on implementing the baseline roll minimization procedure on simulated time-delayed spectra indicated that the peak heights and areas were between 91% and 97% in magnitude when compared with the same peaks in the nondelayed spectra. The correction procedure was also assessed on clinical in vivo spectra. Nonlocalized 31P MR spectra of the liver were obtained with and without an acquisition delay of 2.1 ms, and the time delayed spectra subjected to the baseline minimization routine. Metabolite peak heights and areas in the corrected spectra were approximately 94% in magnitude when compared with the same peaks in the original nondelayed whole volume spectra. Implementation of the baseline minimization procedure on in vivo localized spectra with varying signal to noise ratios produced good results. It takes approximately 13 s to implement the baseline roll minimization procedure. In this paper, the technique will be referred to as BaseLine Artifact Suppression Technique (BLAST) routine.

Artifacts↗