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The development of attribute dominance in the knowledge base.

Two cuing, free-recall studies were conducted to test Bach and Underwood's (1970) hypothesis that acoustic encoding is dominant among second graders and semantic encoding is dominant among sixth graders. When retrieval cues were presented with to-be-remembered items at both input and output (Experiment 1), and when cues were presented only at output (Experiment 2), semantic cues were more efficient in elevating recall than were acoustic cues for both second and sixth graders. When these and other results generally found using recognition, sorting, incidental learning, and free-recall experimental designs are compared, it seems plausible that item presentation and memory-testing formats interact with age, and that these factors account for the different patterns of attribute dominance found in the literature. The knowledge base cannot be understood by focusing on either subject or task analyses, but only by focusing on interactions between subject and task variables as they change over time. The educational implications for young grade-school children are discussed.

Attention↗

A knowledge-based time-oriented active database approach for intelligent abstraction, querying and continuous monitoring of clinical data.

Query and interpretation of time-oriented medical data involves two subtasks: Temporal-reasoning--intelligent analysis of time-oriented data, and temporal-maintenance--effective storage, query, and retrieval of these data. Integration of these tasks into one system, known as temporal-mediator, has been proven to be beneficial to biomedical applications such as monitoring, therapy, quality assessment, visualization and exploration of time-oriented data. One potential problem in existing temporal-mediation approaches is lack of sufficient responsiveness when querying or continuously monitoring the database for complex abstract concepts that are derived from the raw data, especially regarding a large patient group. We propose a new approach: the knowledge-based time-oriented active database, a temporal extension of the active-database concept, and a merger of temporal reasoning and temporal maintenance within a persistent database framework. The approach preserves the efficiency of databases in handling data storage and retrieval, while enabling specification and performance of complex temporal reasoning using an incremental-computation approach. We implemented our approach within the Momentum system. Initial experiments are encouraging; an evaluation is underway

Algorithms↗

A knowledge-based method for reducing attenuation artefacts caused by cardiac appliances in myocardial PET/CT.

Attenuation artefacts due to implanted cardiac defibrillator leads have previously been shown to adversely impact cardiac PET/CT imaging. In this study, the severity of the problem is characterized, and an image-based method is described which reduces the resulting artefact in PET. Automatic implantable cardioverter defibrillator (AICD) leads cause a moving-metal artefact in the CT sections from which the PET attenuation correction factors (ACFs) are derived. Fluoroscopic cine images were measured to demonstrate that the defibrillator's highly attenuating distal shocking coil moves rhythmically across distances on the order of 1 cm. Rhythmic motion of this magnitude was created in a phantom with a moving defibrillator lead. A CT study of the phantom showed that the artefact contained regions of incorrect, very high CT values and adjacent regions of incorrect, very low CT values. The study also showed that motion made the artefact more severe. A knowledge-based metal artefact reduction method (MAR) is described that reduces the magnitude of the error in the CT images, without use of the corrupted sinograms. The method modifies the corrupted image through a sequence of artefact detection procedures, morphological operations, adjustments of CT values and three-dimensional filtering. The method treats bone the same as metal. The artefact reduction method is shown to run in a few seconds, and is validated by applying it to a series of phantom studies in which reconstructed PET tracer distribution values are wrong by as much as 60% in regions near the CT artefact when MAR is not applied, but the errors are reduced to about 10% of expected values when MAR is applied. MAR changes PET image values by a few per cent in regions not close to the artefact. The changes can be larger in the vicinity of bone. In patient studies, the PET reconstruction without MAR sometimes results in anomalously high values in the infero-septal wall. Clinical performance of MAR is assessed by two physicians' inspection of images generated in 30 patients with and without MAR. Noticeable image differences are judged in 14 of 28 (50%) observations with AICD leads, and significant clinical impact is judged in 2 of 28 (7%) of those observations. A polar map analysis shows significant differences in 10 of 14 (71%) studies with AICD leads, and 0 of 16 (0%) studies without AICD leads. These results show that the MAR method is successful in reducing the magnitude of the metal artefact without incorrectly altering cases without metal artefact. In spite of profound changes to the CT image from the moving metal, the PET ACF in that study was changed by no more than 20%.

Artifacts↗

The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics.

Expression profiles of 5058 human gene transcripts represented by an array of 7451 clones from the first IMAGE Consortium cDNA library from infant brain have been collected by semiquantitative hybridization of the array with complex probes derived by reverse transcription of mRNA from brain and five other human tissues. Twenty-one percent of the clones corresponded to transcripts that could be classified in general categories of low, moderate, or high abundance. These expression profiles were integrated with cDNA clone and sequence clustering and gene mapping information from an upgraded version of the Genexpress Index. For seven gene transcripts found to be transcribed preferentially or specifically in brain, the expression profiles were confirmed by Northern blot analyses of mRNA from eight adult and four fetal tissues, and 15 distinct regions of brain. In four instances, further documentation of the sites of expression was obtained by in situ hybridization of rat-brain tissue sections. A systematic effort was undertaken to further integrate available cytogenetic, genetic, physical, and genic map informations through radiation-hybrid mapping to provide a unique validated map location for each of these genes in relation to the disease map. The resulting Genexpress IMAGE Knowledge Base is illustrated by five examples presented in the printed article with additional data available on a dedicated Web site at the address http://idefix.upr420.vjf.cnrs.fr/EXPR++ +/ welcome.html.

Brain Chemistry↗

Evidence for knowledge-based category discrimination in infancy.

Two studies examined whether infants' category discrimination in an object-examination task was based solely on an ad hoc analysis of perceptual similarities among the experimental stimuli. In Experiment 1A, 11-month-olds examined four different exemplars of one superordinate category (animals or furniture) twice, followed by a new exemplar of the familiar category and an exemplar of the contrasting category. Group A (N = 39) explored natural-looking toy replicas with low between-category similarity, whereas group B (N = 40) explored artificial-looking toy models with high between-category similarity. Experiment 1B (N = 40) tested a group of 10-month-olds with the same design. Experiment 1C (N = 20) reversed the order of test trials. For Experiment 2 (N = 20), the same artificial-looking toy animals as in Experiment 1 (group B) were used for familiarization), but no category change was introduced at the end of the session. Infants' responses varied systematically only with the presence of a category change, and not with the degree of between-category similarity. This supports the hypothesis that performance was knowledge based.

Adult↗

A novel strategy for the synthesis of the cysteine-rich protective antigen of the malaria merozoite surface protein (MSP-1). Knowledge-based strategy for disulfide formation.

The most promising antigen for a protective malaria vaccine is a cysteine-rich domain at the carboxyl terminus of the merozoite surface protein (MSP-1). Passive transfer of anti-MSP-1 antibody or immunization of MSP-1 against infection challenge confers protection in primate and rodent models. The antigen belongs to the three-disulfide epidermal growth factor (EGF) family based on the alignment of the six cysteines. In the K1 strain there are, however, only four cysteines corresponding to the four carboxyl cysteines of EGF. Furthermore, disulfide pairing would produce a non-EGF pattern. Because this cysteine-rich antigen is conformation-dependent, and reduction of the disulfide bonds abolishes antigenicity, we used a synthetic analog to investigate the probable disulfide pairing of this antigen. This paper describes the synthesis, folding and disulfide pairings of two 50-residue cysteine-rich peptides. One contains two disulfides (VK-50) derived from the native sequence of MSP-1 of the Thailand K1 strain (aa 1629-1679). The other contains an EGF-like, three-disulfide [Cys-9,14]VK-50 peptide. Both peptides were synthesized by a solid-phase method using Fmoc-chemistry. The crude peptide of VK-50 was folded, and the disulfide was oxidized by the DMSO method to obtain a structure with an expected disulfide pairing of 3-4, and 5-6. The specific pairing pattern of 1-3, 2-4 and 5-6 in [Cys 9,14]VK-50 corresponding to EGF in [Cys 9,14]VK-50 was obtained using a 'knowledge-based' (KB) strategy for their formation.(ABSTRACT TRUNCATED AT 250 WORDS)

Amino Acid Sequence↗

Educational applications of a knowledge-based expert system for medical decision making in hepatology.

An expert system for medical decision making in hepatology has been developed with the aim of assisting medical education. The knowledge representation is based on different slots respectively concerned with structural and protypical description, and system control. Reasoning is performed at two levels considering in sequence syndromes and diseases. Explanations are available at any time during the reasoning process. Educational facilities are provided by using the help sections of the system, which include definitions and descriptions of finding in both health and disease, as well as summaries defining essential clinical and pathophysiological features of all diagnostic hypotheses. The system provides the following educational functions: support to medical decision making, differential diagnosis, knowledge-base consultation, system description and clinical simulation. A good correspondence was found between the conclusions and suggestions provided by the system and those of the attending physicians. The program, which was written in PROLOG and developed under MS-DOS Operating System, runs on IBM-compatible personal computers equipped with hard-disk and mouse.

Computer Systems↗

Trauma base knowledge and the effect of the trauma evaluation and management program among senior medical students in seven countries.

BACKGROUND: We compared base trauma knowledge and the impact of the Trauma Evaluation and Management (TEAM) program among senior medical students in seven countries. METHODS: We compared pre- and post-TEAM multiple choice question scores of fourth-year students in Jamaica (n = 32), Trinidad (n = 32), Costa Rica (n = 64), Australia (n = 35), United Arab Emirates (n = 68), Toronto (n = 29) and Pennsylvania (n = 34). Means and degree of improvement were compared by analysis of variance (p < 0.05 for statistical significance). Percentage pass (based on 70% or 60% pass mark), student's perception of instruction level, and grading of TEAM (based on the percentage of students grading 1-5 for each category) were assessed by chi2 analysis. [table: see text]. RESULTS: Only 31.4% of students achieved the borderline pass mark of 60%, and 5.4% achieved a clear pass mark of 70%. The performance before and after TEAM was quite variable among medical schools. A grade of > or = 4 was assigned by 74% to 100% for objectives, knowledge improvement, satisfaction, and recommending TEAM for the curriculum. TEAM was rated "just right" by 70.3% to 92.7%, "too simple" by 1.6% to 21.6%, and "too advanced" by 3.3% to 13.5% of students. CONCLUSION: Base trauma knowledge in these students, though variable, was generally very low and improved with TEAM. Our data suggest a need for greater undergraduate emphasis in trauma education.

Analysis of Variance↗

A modular knowledge base for the follow-up of clinical protocols.

From the knowledge engineering point of view, the observation of patients subjected to clinical protocols of therapy constitutes a domain characterized by the existence of strongly structured knowledge. We have approached the problem from the perspective of a homogeneous and modular knowledge representation theory, based on the concept of Generalized Magnitude. This concept arises from identifying and collecting all possible facts of a domain established a priori, and being inspired by the concept of physical magnitudes. The Generalized Magnitudes scheme includes temporal extensions necessary to solve a medical problem for which exists a therapy and a follow-up plan with temporal specifications, and also facilitates the creation of advisory expert systems.

Drug Therapy, Computer-Assisted↗

Challenges in implementing a knowledge editor for the Arden Syntax: knowledge base maintenance and standardization of database linkages.

CONTEXT: Incorporation of research findings into clinical practice lags behind their dissemination in the medical literature. Arden Syntax is a standard that could be used to encode evidence in a clinical decision support system (CDSS). However, dissemination of knowledge is hampered by lack of standard linkages to clinical databases. OBJECTIVE: To create a knowledge editor that facilitates transfer of knowledge from the medical literature to clinical practice via a CDSS. METHODS: Using a Web browser-based application, we implemented linkages to MEDLINE to permit queries on demand and registration of queries to be executed periodically, with results copied into Arden Medical Logic Modules (MLMs). To facilitate standardization of MLMs, database linkages are encoded using emerging HL7 standards such as a data model (virtual medical record). CONCLUSIONS: A Web-based application can facilitate transfer of knowledge into clinical practice and knowledge base maintenance through periodic queries and deployment of standards for knowledge representation.

Artificial Intelligence↗

Knowledge-based design of a soluble bacteriorhodopsin.

Much knowledge has been accrued from high resolution protein structures. This knowledge provides rules and guidelines for the rational design of soluble proteins. We have extracted these rules and applied them to redesigning the structure of bacteriorhodopsin and to creating blueprints for a monomeric, soluble seven-helix bundle protein. Such a protein is likely to have desirable properties, such as ready crystallization, which membrane proteins lack and an internal structure similar to that of the native protein. While preserving residues shown to be necessary for protein function, we made modifications to the rest of the sequence, distributing polar and charged residues over the surface of the protein to achieve an amino acid composition as akin to that of soluble helical proteins as possible. A secondary goal was to increase apolar contacts in the helix intercalation regions of the protein. The scheme used to design the model sequences requires knowledge of the number and orientation of helices and some information about interior contacts, but detailed structural knowledge is not required to use a scheme of this type.

Amino Acid Sequence↗

Framemed, a prototypical medical knowledge base of unusual design.

Carefully structured medical knowledge can be used for a variety of purposes, including medical records, drug and test ordering, and differential diagnosis. The Framemed system divides medical information into 26 domains and arranges the items in a hierarchical sequence. The knowledge in the system resides in descriptive, relational, and conditional records created by experts in the various domains, who must sign and date each record as it is developed and are entirely responsible for its contents. Formation of the hierarchies requires careful attention to concepts and yields a logical framework for a standardized terminology that is in the public domain.

Artificial Intelligence↗

Knowledge-based client-server approach to structural information retrieval: the Digital Anatomist Browser.

Structural information can be defined as data and knowledge about biological objects ranging in size from molecules to the whole body. A framework is described for organizing structural information around a well-defined set of terminology and semantic relationships, and for disseminating multimedia structural information by means of a wide-area information server that is accessible over the internet. A Macintosh-based client of this server, called the Digital Anatomist Browser, has been used to teach neuroanatomy for the last 2 years. The client-server approach provides each student unlimited access to a rapidly growing knowledge base of structural biology that, while immediately useful for anatomy teaching, has the potential to be an organizing framework for other kinds of medical knowledge as well.

Artificial Intelligence↗

Ontology-based knowledge repository support for healthgrids.

Healthgrids unite a large amount of independent and distributed organisations to provide for various healthcare services. Often the involved organisations can belong to different areas of healthcare and even different countries. However to achieve efficient operation they have to act in a well coordinated manner. As a result, an efficient knowledge sharing between multiple participating parties of the healthgrid is required. The paper describes application of an earlier developed ontology-driven KSNet (Knowledge Source Network) - approach to knowledge repository support for healthgrids. This approach is based on representation of knowledge via ontologies using formalism of object-oriented constraint networks. Such representation makes it possible to define and solve various tasks from the areas of management, planning, configuration, etc., by using constraint solving engines such as, for instance, ILOG or CLP. The major discussed aspects cover the formalism of knowledge representation via ontologies and implementation of the approach as a decision support system for a case study from the area of health service logistics.

Artificial Intelligence↗

Using statistical and knowledge-based approaches for literature-based discovery.

The explosive growth in biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. While researchers formulate new hypotheses to test, it is very important for them to identify connections to their work from other parts of the literature. However, the current volume of information has become a great barrier for this task and new automated tools are needed to help researchers identify new knowledge that bridges gaps across distinct sections of the literature. In this paper, we present a literature-based discovery system called LitLinker that incorporates knowledge-based methodologies with a statistical method to mine the biomedical literature for new, potentially causal connections between biomedical terms. We demonstrate LitLinker's ability to capture novel and interesting connections between diseases and chemicals, drugs, genes, or molecular sequences from the published biomedical literature. We also evaluate LitLinker's performance by using the information retrieval metrics of precision and recall.

Abstracting and Indexing↗

First multi-centre evaluation of a knowledge-based implant-assistant for implantable cardioverter-defibrillators.

AIMS: Modern implantable cardioverter-defibrillators (ICDs) place increasing demands on the physician, as their complexity requires more and more knowledge and effort in handling them. To overcome this problem an implant-assistant has been developed, which transfers clinical data entered by the physician into a complete set of parameters for programming a dual-chamber ICD (Tachos-DR, Biotronik, Berlin, Germany) at DFT testing (DFT-Prog) and first permanent programming (Perm-Prog) after implant. METHODS AND RESULTS: Routine ICD implantations were initially evaluated by clinical experts at 19 centres in USA and Europe from 178 patient files. The rating of parameters was related to the number of parameters available in each patient. For DFT-Prog, 98.4% of parameter suggestions were identical to experts' expectations, an additional 1.0% were accepted, 0.5% were rejected, and none was considered harmful. This resulted in an overall acceptance of 94.4% of the DFT-Prog. For Perm-Prog, 96.1% of parameters were identical to those advised by experts, an additional 2.4% were accepted, 1.5% rejected, and seven parameters (0.04%) were considered potentially harmful by experts with an overall acceptance of 86.5%. Adaptation of the implant-assistant increased the overall acceptance to 100% for DFT-Prog and 90.6% for first Perm-Prog without any potentially harmful suggestions. CONCLUSION: The ICD implant-assistant, which allows the physician to programme ICDs directly from clinical data, is a promising method to simplify the programming of modern ICDs.

Defibrillators, Implantable↗

Evaluating the web as a clinical knowledge base.

Medical diagnostic decision support systems are some of the most visible applications of medical informatics. Many of these systems, however, were created in the pre-WWW era, when access to clinical knowledge was much more limited than it is currently. Using the Google(tm) Java API1, we created a simple program to extract potential diagnoses from a general web search. Our system performed at a level comparable to other medical expert systems.

Algorithms↗