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Results for “Knowledge base”

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At least 1,405 records · Page 78Linked to original sources

PubMed2004

Development of required postgraduate palliative care training for internal medicine residents and medical oncology fellows.

BACKGROUND: The need for better care for terminally ill patients led us to create an educational program to provide internal medicine residents and medical oncology fellows basic competency in palliative and end-of-life care. METHODS: An interdisciplinary team identified educational strategies, course objectives, content, and evaluation instruments. RESULTS AND CONCLUSIONS: Our strategy is to use a required Web-based course to establish a knowledge base upon which specific training during clinical rotations build skills. Field testing of the Web course showed it was an effective tool for delivering clinically applicable content. Skill building experiences are now being integrated into selected clinical rotations.

Attitude of Health Personnel↗

PubMed2003

Representing complexity in part-whole relationships within the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA) is a frame-based ontology that represents declarative knowledge about the structural organization of the human body. Part-whole relationships play a particularly important role in this representation. In order to assure that knowledge-based applications relying on the FMA as a resource can reason about anatomy, we have modified and enhanced currently available schemes of meronymic relationships. We have introduced and defined distinct partitions for decomposing anatomical structures and attributed the part relationships in order to eliminate ambiguity and enhance specificity in the richness of meronymic relationships within the FMA.

Anatomy↗

PubMed2006

Structural visualization of expert nursing: Development of an assessment and intervention algorithm for delirium following abdominal and thoracic surgeries.

An assessment and intervention algorithm for delirium following abdominal and thoracic surgeries was developed based upon the current knowledge-base. The sources of information included literature and clinical expertise. The assessment and intervention algorithm was structured and visualized so that patient-tailored and risk-stratified prediction/prevention, assessment, and intervention could be carried out. Accumulation of clinical outcome data is necessary in the future validation study to identify the relative weight of risk factors and clinical utility of the algorithm.

Abdomen↗

PubMed1993

HYCONES: a hybrid connectionist expert system.

This paper describes HYCONES, a tightly-coupled Hybrid Connectionist Expert System that integrates neural networks with a symbolic approach (frames). The symbolic paradigm provides rich and flexible constructs to describe the domain knowledge, while the connectionist one provides the system with learning capabilities. The paper describes the architecture of the system, focusing on the hybrid aspects of the knowledge base and on its automatic knowledge acquisition technique from a case database. The first validation of the system is presented. At the end, a comparison with related research efforts and future developments are discussed.

Database Management Systems↗

PubMed1998

Hypertextual navigation operationalizing generic clinical practice guidelines for patient-specific therapeutic decisions.

Despite the proliferation of implemented clinical practice guidelines, there is still little evidence of physicians compliance to formal standards. The ONCODOC project proposes a framework for elaborating generic decision support guidelines in a document-based paradigm with a knowledge-based approach. It has been first applied to assist clinicians in the treatment of breast cancer patients. Therapeutic expertise has been encoded as a decision tree. The decision process is driven by the clinician who interactively browses a hypertext version of the decision tree. During the navigation, he incrementally assigns values to decision parameters on the basis of his free interpretation of his patient's condition and thus builds a clinical context leading to patient-specific therapeutic recommendations. These guidelines are distributed on a hospital intranet and are evaluated at the point of care in an oncology department.

Breast Neoplasms↗

PubMed1998

Will evidence-based nursing practice make practice perfect?

Evidence-based practice, or evidence-based decision-making, is rapidly developing as a growth industry in nursing and the health professions more widely. It has its origins in the work of the British epidemiologist Archie Cochrane and has recently been re-energized in Canada by the National Forum on Health and its call for a culture of evidence-based decision-making. Before we adopt evidence-based nursing (EBN) as a mantra for the 21st century, we should examine its origins and its consequences, and we should probe related concepts, 2 of which are the nature and structure of practice-based knowledge and the nature and structure of evidence generally. Findings of a recent survey of nurses in western Canada are used to illustrate that nurses use a broad range of practice knowledge, much of which is experientially based rather than research-based.

Adult↗

PubMed1999

Happy birthday DIOGENE: a hospital information system born 20 years ago.

Since its birth in 1978, DIOGENE, the hospital information system of Geneva University Hospital has been constantly evolving, with a major change in 1995, when migrating from a centralized to an open distributed architecture. For a few years, the hospital had to face health policy revolution with both economical constraints and opening of the healthcare network. The hospital information system DIOGENE plays a significant role by integrating four axes of knowledge: medico-economical context for better understanding and influencing resources consumption; the whole set of patient reports and documents (reports, encoded summaries, clinical findings, images, lab data, etc.), patient-dependent knowledge, in a vision integrating time and space; external knowledge bases such as Medline (patient-independent knowledge); integration of these patient-dependent and independent knowledge in a case-based reasoning format, providing on the physician desktop all relevant information for helping him to take the most appropriate adequate decision.

Computer Systems↗

PubMed1998

Happy birthday DIOGENE: a hospital information system born 20 years ago.

Since its birth in 1978, DIOGENE, the Hospital Information System of Geneva University Hospital has been constantly evolving, with a major change in 1995, when migrating from a centralized to an open distributed architecture. Since a few years, the hospital had to face health policy revolution with both economical constraints and opening of the healthcare network. The Hospital Information System DIOGENE plays a significant role by integrating four axes of knowledge medico-economical context for better understanding and influencing resources consumption the whole set of patient reports and documents (reports, encoded summaries, clinical findings, images, lab data, etc.) patient-dependent knowledge, in a vision integrating time and space external knowledge bases such as Medline (patient-independent knowledge) integration of these patient-dependent and -independent knowledges in a Case-Based Reasoning format, providing on the physician desktop all relevant information for helping him to take the most appropriate adequate decision.

Hospital Costs↗

PubMed1996

Knowledge acquisition for temporal abstraction.

Temporal abstraction is the task of detecting relevant patterns in data over time. The knowledge-based temporal-abstraction method uses knowledge about a clinical domain's contexts, external events, and parameters to create meaningful interval-based abstractions from raw time-stamped clinical data. In this paper, we describe the acquisition and maintenance of domain-specific temporal-abstraction knowledge. Using the PROTEGE-II framework, we have designed a graphical tool for acquiring temporal knowledge directly from expert physicians, maintaining the knowledge in a sharable form, and converting the knowledge into a suitable format for use by an appropriate problem-solving method. In initial tests, the tool offered significant gains in our ability to rapidly acquire temporal knowledge and to use that knowledge to perform automated temporal reasoning.

Artificial Intelligence↗

PubMed2005

Detecting possible vaccination reactions in clinical notes.

The Vaccine Safety Datalink is a collaboration between the CDC and eight large HMO's to investigate adverse events following immunization through analysis of medical care databases and patients' medical charts. We modified an existing system called MediClass that uses natural language processing (NLP) and knowledge-based methods to classify clinical encounters recorded in electronic medical records (EMRs). We developed the knowledge necessary for MediClass to detect possible vaccine reactions in the outpatient, ED, and telephone encounters recorded in the EMR of a large HMO. We first trained the system using a manually coded gold standard training set, and achieved high sensitivity and specificity. We then ran a large set of post-immunization encounter records through MediClass to see if our method would generalize. Compared to methods that use administrative and clinical codes assigned to the EMR by clinicians, the system significantly improves the positive predictive value for detecting possible vaccine reactions.

Adverse Drug Reaction Reporting Systems↗

PubMed2002

Tracheal suctioning: an exploration of nurses' knowledge and competence in acute and high dependency ward areas.

BACKGROUND AND RATIONALE: With an increasing demand for intensive care beds more nurses in acute and high dependency wards will be expected to care competently for patients with tracheostomy tubes. Tracheal suctioning is an essential aspect of effective airway management. However, this has many associated risks and complications, ranging from trauma and hypoxaemia to, in extreme cases, cardiac arrest and death. It is imperative that nurses are aware of these risks and are able to practice according to current research recommendations. Aims. This study was designed to explore nurses' knowledge and competence in performing tracheal suctioning in acute and high dependency ward areas and to investigate discrepancies between knowledge and practice using method triangulation. METHODS: Twenty-eight nurses were observed using nonparticipant observation and a structured observation schedule. Each subject was interviewed and questioned about their tracheal suctioning practices, and subsequently completed a knowledge-based questionnaire. Scores were allocated for knowledge and practice. FINDINGS: The findings demonstrated a poor level of knowledge for many subjects. This was also reflected in practice, as suctioning was performed against many of the research recommendations. Many nurses were unaware of recommended practice and a number demonstrated potentially unsafe practice. In addition, there was no significant relationship between knowledge and practice. However, during the interviews, many nurses were able to provide a rationale for specific aspects of practice that were perhaps not based on current research recommendations. CONCLUSIONS: The study raised concern about all aspects of tracheal suctioning and has highlighted the need for changes in practice, clinical guidelines and focused practice-based education.

Clinical Competence↗

PubMed2002

Terminology-driven literature mining and knowledge acquisition in biomedicine.

In this paper we describe Tagged Information Management System (TIMS), an integrated knowledge management system for the domain of molecular biology and biomedicine, in which terminology-driven literature mining, knowledge acquisition (KA), knowledge integration (KI), and XML-based knowledge retrieval are combined using tag information management and ontology inference. The system integrates automatic terminology acquisition, term variation management, hierarchical term clustering, tag-based information extraction (IE), and ontology-based query expansion. TIMS supports introducing and combining different types of tags (linguistic and domain-specific, manual and automatic). Tag-based interval operations and a query language are introduced in order to facilitate KA and retrieval from XML documents. Through KA examples, we illustrate the way in which literature mining techniques can be utilised for knowledge discovery from documents.

Artificial Intelligence↗

PubMed1990

Prediction of homologous protein structures based on conformational searches and energetics.

A "knowledge-based" method of predicting the unknown structure of a protein from a homologous known structure using energetics to determine a sidechain conformation is proposed. The method consists of exchanging the residues in the known structure for the sequence of the unknown protein. Then a conformational search with molecular mechanics energy minimization is done on the exchanged residues. The lowest energy conformer is the one picked to be the predicted structure. In the structure of bovine trypsin, the importance of including a solvation energy term in the search is demonstrated for solvent accessible residues, while molecular mechanics alone is enough to correctly predict the conformation of internal residues. The correctness of the model is assessed by a volume error overlap of the predicted structure compared to the crystal structure. Finally, the structure of rat trypsin is predicted from the crystal structure of bovine trypsin. The sequences of these two proteins are 74% identical and all of the significant changes between them are on external residues. Thus, the inclusion of solvation energy in the conformational search is necessary to accurately predict the structure of the exchanged residues.

Animals↗

PubMed1999

EICO-1: an orthodontist-maintained expert system in clinical orthodontics.

Expert systems are increasingly being used to provide comprehensive interpretative services for diagnosis and treatment planning. Some of these systems are constrained by the complexities of rule-based strategies and a need for knowledge engineers throughout the maintenance phase. A new approach to knowledge acquisition known as Ripple-Down-Rules was used in the development of EICO-1 (Expert Interpretation in Clinical Orthodontics). This expert-maintained system for automating orthodontic reports has a knowledge base of six hundred and eighty rules, and is maintained by an expert trained only in Orthodontics and without the help of knowledge engineers. EICO-1 is the first expert system in Dentistry to use Ripple-Down-Rules. It has potential as an interactive advisory tool and is applicable in a clinical situation.

Artificial Intelligence↗

PubMed2000

Non-invasive positive pressure ventilation in acute respiratory failure: providing competent care.

Non-invasive positive pressure ventilation (NPPV) has been used as an alternative strategy to provide ventilatory support for patients with acute respiratory failure. Most studies demonstrate that the use of NPPV in acute respiratory failure results in a reduction in the need for endotracheal intubation and an overall survival advantage. However, current evidence, in the form of randomised controlled trials, suggests that these benefits may be restricted to patients suffering from acute exacerbation of chronic obstructive pulmonary disease (COPD). The clinical application of NPPV involves the development of competence in delivering the particular intervention. Clinical outcomes and thus valid comparisons with alternate methods of ventilatory support can only be made if attention is paid to the clinical indications for the application of NPPV and patient subgroups it is used to treat and the level of competence of care givers in its application and delivery. One essential element of competence is the establishment of an appropriate knowledge base and the development of clinical practice guidelines. This literature review identifies the current indications for NPPV and the relevant information for developing clinical practice guidelines for the management of this form of ventilatory support.

Acute Disease↗

PubMed2005

Semantic clinical guideline documents.

Decision-support systems based on clinical practice guidelines can support physicians and other healthcare personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner,perform consistency checks, and use the guidelines directly in decision-support systems.Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support.

Decision Making, Computer-Assisted↗

PubMed2005

Managing knowledge to support the patient journey in NHS Scotland: strategic vision and practical reality.

BACKGROUND: The strategy for NHS Scotland Knowledge Services is set in the context of a global transition to a networked model of management within health services. OBJECTIVES: Development planning for NHS Scotland aims to establish strategic vision and operational delivery systems which meet the needs of this changing health environment. METHODS: Analysis of knowledge needs at strategic organizational level and through consultation with healthcare staff form the basis of a vision of seamless knowledge support throughout all stages of the patient journey, based on a hybrid model of complementary human- and technology-based knowledge networks. RESULTS: The central role of the NHS Scotland e-library as a system-wide technology infrastructure facilitating management of both explicit and tacit knowledge is described. The implementation pathway and approaches to evaluation are outlined, based on practical steps to translate the concept of knowledge networks into a working reality. CONCLUSIONS: The model emerging is that of a knowledge matrix, with the primary delivery system comprising inter-dependent human, organizational and technology-based networks focused on the overriding common purpose of improving patient care.

Computer Communication Networks↗

PubMed2004

Visual feature learning in artificial grammar classification.

The Artificial Grammar Learning task has been used extensively to assess individuals' implicit learning capabilities. Previous work suggests that participants implicitly acquire rule-based knowledge as well as exemplar-specific knowledge in this task. This study investigated whether exemplar-specific knowledge acquired in this task is based on the visual features of the exemplars. When a change in the font and case occurred between study and test, there was no effect on sensitivity to grammatical rules in classification judgments. However, such a change did virtually eliminate sensitivity to training frequencies of letter bigrams and trigrams (chunk strength) in classification judgments. Performance of a secondary task during study eliminated this font sensitivity and generally reduced the contribution of chunk strength knowledge. The results are consistent with the idea that perceptual fluency makes a contribution to artificial grammar judgments.

Artificial Intelligence↗