PubMed Health⌕ Search

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 1,207 records · Page 67Linked to original sources

Internet-based decision-support server for acute abdominal pain.

The paper describes conception and prototypical design of a decision-support server for acute abdominal pain. Existing formal methods to develop and exchange scores, guidelines and algorithms are used for integration. For scoring systems a work-up to separate terminological information from structure is described. The terminology is separately stored in a data dictionary and the structure in a knowledge base. This procedure enables a reuse of terminology for documentation and decision-support. The whole system covers a decision-support server written in C++ with underlying data dictionary and knowledge base, a documentation module written in Java and a CORBA middleware that establishes a connection via Internet.

Abdominal Pain↗

Understanding stereotactic radiosurgery for intracranial tumors, seed implants for prostate cancer, and intravascular brachytherapy for cardiac restenosis.

Our 21st century has moved us into a world of technology never imagined. The aim of our article is to move oncology nurses beyond the realm of external beam radiation therapy. We chose to present 3 modalities of high precision that are infiltrating the everyday world of radiation therapy. Stereotactic radiosurgery for intracranial brain tumors and brachytherapy for prostate cancer require an expanded knowledge base for nursing to deliver excellent patient care. Cardiac patients receiving radiation seeds is new in the world of oncology nursing. These patients are unique but they are now a part of our world. Expanding our knowledge base to include a radiation procedure in cardiac care does bring us beyond the world of external beam radiation. Patients often seek information from nurses. Having an understanding of the basic principles and techniques will enable oncology nurses to educate patients. The purpose of this article is to explain the procedure of stereotactic radiosurgery, brachytherapy for prostate cancer, and intravascular brachytherapy for cardiac restenosis. Our discussion will include selection criteria, potential sides effects and risks, and nursing care.

Brachytherapy↗

Comprehensive computerised primary care records are an essential component of any national health information strategy: report from an international consensus conference.

In many countries, primary care informatics has developed to the point that it is recognised as an important enabler of quality improvement; this has not occurred to date in the United States. With this conference, we aimed to build an international consensus as to whether primary care has unique characteristics that require an informatics subspecialty; and, if so, to establish the role of primary care informatics in improving patient care, and to enable its recognition in the national strategy.The conference was organised by the primary care informatics working groups of AMIA, EFMI, IMIA and Wonca and took place at Medinfo 2004 in San Francisco. It consisted of two plenary lectures, two small-group work sessions and a panel discussion to summarise the day. It was attended by an international audience of 53 health informaticians, mostly working in primary care. There was consensus among the participants that primary care has many unique characteristics that justify the existence of an informatics subspecialty: primary care informatics (PCI). The conference identified principles and practical examples of: (1) the effective deployment of information technology to underpin the provision of records, communication and access to information; (2) the need to harness the extensive knowledge base about the practice of PCI; and (3) the contribution of the experimental work and theory that underpins the science of PCI. These principles and examples of their practical application were largely derived from the extensive knowledge base which has been built up in countries that have developed PCI over the last one to two decades.

Health Policy↗

DXplain. An evolving diagnostic decision-support system.

DXplain is an evolving computer-based diagnostic decision-support system designed for use by the physician who has no computer expertise. DXplain accepts a list of clinical manifestations and then proposes diagnostic hypotheses. The program explains and justifies its interpretations and provides access to a knowledge base concerning the differential diagnosis of the signs and symptoms. DXplain was developed with the support and cooperation of the American Medical Association. The system is distributed to the medical community through AMA/NET--a nationwide computer communications network sponsored by the American Medical Association--and through the Massachusetts General Hospital Continuing Education Network. A key element in the distribution of DXplain is the planned collaboration with its physician-users whose comments, criticisms, and suggestions will play an important role in modifying and enhancing the knowledge base.

Artificial Intelligence↗

A possible neural mechanism underlying consciousness based on the pattern processing capabilities of pyramidal neurons in the cerebral cortex.

This paper examines a possible neural mechanism underlying the phenomenon of consciousness by exploring the ability of cortical pyramidal cells to process patterns of information. A numerical model of a section of a neuron is described that enables the transient membrane potential distribution to be predicted following inputs to the cell. The neuron model incorporates learning by modelling the ability of dendritic spine receptors to undergo changes in their sensitivity if they receive inputs when their local membrane is depolarized. Simulations show the cell to be capable of recognizing patterns amongst its inputs, and to be able to extend its repertoire of learnt patterns by associating one pattern of inputs with another. These pattern processing capabilities can take place within the apical dendritic tree, whilst the soma sees a much attenuated and slower response that reflects the general level of pattern recognition taking place in the dendrites. It is argued here that the distribution of patterns stored in the apical dendrites of all the pyramidal cells represents the cortical knowledge base. Incoming patterns of information are compared with those stored in the cortical knowledge base to pick out components that have been experienced before. The resulting distribution of soma responses represents the way the incoming patterns of information are perceived. Most of the patterns learnt arise from other pyramidals and represent information about cortical behaviour itself. The distribution of soma responses therefore represents a perception of the self as well as a perception of the environment. It is argued here that this intimate perception of the self could underlie the phenomenon of consciousness.

Cerebral Cortex↗

AI/RHEUM. A consultant system for rheumatology.

A knowledge-based computer consultant system in the medical specialty area of rheumatology is described. The system, called AI/RHEUM, uses artificial intelligence techniques to provide nonrheumatologist physicians with diagnostic assistance in this specialty area. AI/RHEUM contains in a structured knowledge base formal criteria for 26 rheumatologic diseases. The system has been retrospectively tested against 384 clinical cases, with an overall correct diagnostic performance of 94%.

Computers↗

Problems in shortening the time to confirmation of ALS diagnosis: lessons from the 1st Consensus Conference, Chicago, May 1998.

The 2nd Consensus Conference (Versailles) on the early diagnosis of amyotrophic lateral sclerosis (ALS) developed themes identified at the 1st Consensus Conference (Chicago) on defining optimal management in ALS. These themes included describing the problems and limitations in current diagnostic practices, identifying consequences of early diagnosis on patient management, establishing recommendations to help healthcare personnel achieve the early diagnosis and proposing solutions to facilitate early diagnosis of ALS. Lessons from the ISIS Survey and the 1st Consensus Conference focused on the variability of the first-contact physician, supply factors for specialists and variability of application of medical techniques. The recently introduced concept of 'ALS health states or stages' was reviewed in terms of ongoing and potential prospective studies. The relative contribution of neuroimaging or clinical neurophysiological investigations to accelerating the diagnosis of ALS in clinical practice was debated. The role of a common ALS knowledge-base among patients, initial healthcare providers, diagnosing neurologists and confirming neurologists was critically appraised with regard to simplified 'ALS diagnostic algorithm', 'ten aphorisms in the diagnosis of ALS' and 'ALS axioms of referral'. Refining this ALS knowledge-base is required to identify a minimum dataset required for the evaluation and diagnosis of ALS.

Diagnostic Imaging↗

Coupling the N-CODES system with actual nurse decision-making.

Nurses must be involved in the development and testing of clinical decision support systems if systems that fit into the actual clinical decision-making process and the flow of practice are to be designed. This article discusses the first trial of N-CODES, the Nurse Decision Support System. This system is designed to assist nurses, particularly novices, to make clinical decisions. The adequacy of the theoretical framework and selected aspects of the knowledge base were examined. Twelve nurses participated. Results indicated that revision of the theoretical framework is necessary if it is to be a fair representation of nurse's decision-making. The sequencing of information seems appropriate but the process of developing the knowledge base must be made more transparent to nurse users. After modifications, the next trial will test actual clinical use.

Acute Disease↗

Retrospective validation of a physiological model of glucose-insulin interaction in type 1 diabetes mellitus.

We have previously described a physiological model of glucose-insulin interaction in insulin-dependent (type 1) diabetes mellitus which has been developed for patient and medical staff education about diabetes mellitus, as well as possibly for clinical use. The model attempts to reflect the underlying (patho)physiology of insulin action and carbohydrate absorption in quantitative terms such as insulin sensitivity, volume of glucose and insulin distribution and maximal rate of gastric emptying. The model's predictions also allow a 24 h simulation of patient blood glucose profiles to be generated. Advice is provided by a qualitative knowledge based system which suggests what the next step in improving glycaemic control might be for a given patient, e.g. 'increase before breakfast long-acting insulin by 2 units'. Validation work performed on a previous version of the knowledge based system has demonstrated that it can provide qualitative advice comparable to that of a clinician. Furthermore, bench testing of the predictive accuracy of the model has yielded encouraging results. We therefore set out to perform a preliminary retrospective medical validation of the physiological model using data collected by 30 insulin-dependent diabetic patients attending diabetes out-patient clinics at various centres throughout Europe. We found that the physiological model could only be parameterized for data from 24 (80%) of the 30 patients in the study. Comparison of observed and predicted blood glucose data from these 24 patients over a period of 5-6 days following parameter estimation revealed a mean (+/- SD) root mean square deviation between measured and simulated blood glucose values of 1.93 +/- 0.86 mmol l-1. The implications of these results are discussed.

Blood Glucose↗

A clinical database as a component of a diagnostic hematology workstation.

A clinical database was designed as part of a comprehensive workstation for diagnostic laboratory hematology. The database stores coded findings pertinent to hematologic disorders including inherited abnormalities, previous surgery, malignancies, current therapy, and laboratory test results. The workstation includes knowledge-based systems for peripheral blood analysis, flow cytometry studies, and bone marrow morphology. The peripheral blood system renders an interpretive report based on data from a complete blood count with manual review of a blood smear by a technologist. The flow cytometry module interprets the immunophenotyping and DNA content results, and correlates them with the clinical findings and the peripheral blood data. The bone marrow system bases its report on all of the available information including the morphologic review of the bone marrow specimen by a physician, the peripheral blood data, immunophenotype, and clinical/laboratory findings. Before generating an interpretive report, each of the knowledge-based systems automatically searches the clinical database for specific information pertinent to the findings in the case. Since the workstation must function in situations where access to distributed databases is not feasible or not yet practical, a data entry module with a graphical user interface has been created.

Artificial Intelligence↗

Nurses are what nurses do--are you where you want to be?

Nursing performance, or the skills a nurse exhibits in practice, is limited by the extent or level of a nurse's knowledge base; hence, the expression "nurses are what nurses do" probes nurses' levels of satisfaction with their present educational status. Given the rapid changes in health care today, nurses are questioning their level of commitment to lifelong learning in meeting ever-changing demands. This article examines measures being taken to assess the adequacy of nurses' knowledge base in a field that requires continuous adaptation to change.

Career Choice↗

Assessing children's inference generation: what do tests of reading comprehension measure?

BACKGROUND: Previous research suggests that children with specific comprehension difficulties have problems with the generation of inferences. This raises important questions as to whether poor comprehenders have poor comprehension skills generally, or whether their problems are confined to specific inference types. AIMS: The main aims of the study were (a) using two commonly used tests of reading comprehension to classify the questions requiring the generation of inferences, and (b) to investigate the relative performance of skilled and less-skilled comprehenders on questions tapping different inference types. SAMPLE: The performance of 10 poor comprehenders (mean age 110.06 months) was compared with the performance of 10 normal readers (mean age 112.78 months) on two tests of reading comprehension. METHOD: A qualitative analysis of the NARA II (form 1) and the WORD comprehension subtest was carried out. Participants were then administered the NARA II, WORD comprehension subtest and a test of non-word reading. RESULTS: The NARA II was heavily reliant on the generation of knowledge-based inferences, while the WORD comprehension subtest was biased towards the retention of literal information. Children identified by the NARA II as having comprehension difficulties performed in the normal range on the WORD comprehension subtests. Further, children with comprehension difficulties performed poorly on questions requiring the generation of knowledge-based and elaborative inferences. However, they were able to answer questions requiring attention to literal information or use of cohesive devices at a level comparable to normal readers. CONCLUSIONS: Different reading tests tap different types of inferencing skills. Lessskilled comprehenders have particular difficulty applying real-world knowledge to a text during reading, and this has implications for the formulation of effective intervention strategies.

Child↗

Evaluation of models for the evolution of protein sequences and functions under structural constraint.

In the field of evolutionary structural genomics, methods are needed to evaluate why genomes evolved to contain the fold distributions that are observed. In order to study the effects of population dynamics in the evolved genomes we need fast and accurate evolutionary models which can analyze the effects of selection, drift and fixation of a protein sequence in a population that are grounded by physical parameters governing the folding and binding properties of the sequence. In this study, various knowledge-based, force field, and statistical methods for protein folding have been evaluated with four different folds: SH2 domains, SH3 domains, Globin-like, and Flavodoxin-like, to evaluate the speed and accuracy of the energy functions. Similarly, knowledge-based and force field methods have been used to predict ligand binding specificity in SH2 domain. To demonstrate the applicability of these methods, the dynamics of evolution of new binding capabilities by an SH2 domain is demonstrated.

Computational Biology↗

Integrating large-scale genotype and phenotype data.

With the completion of the Human Genome Project, a new emphasis is focusing on the sequence variation and the resulting phenotype. The number of data available from genomic studies addressing this relationship is rapidly growing. In order to analyze these data as a whole, they need to be integrated, aggregated and annotated in a timely manner. The Pharmacogenetics and Pharmacogenomics Knowledge Base PharmGKB; ( ) assembles and disseminates these data and their associated metadata that are needed for unambiguous identification and replication. Assembling these data in a timely manner is challenging, and the scalability of these data produce major challenges for a knowledge base such as PharmGKB. However, it is only through rapid global meta-annotation of these data that we will understand the relationship between specific genotype(s) and the related phenotype. PharmGKB has confronted these challenges, and these experiences and solutions can benefit all genome communities.

Animals↗

Computer-aided clinical laboratory diagnosis in conjunction with the electronic medical textbook.

1. INTRODUCTION. Medical knowledge has been increasing and diversifying on a worldwide scale, while the specialization of physicians has been extended vigorously. Under this environment, it may be natural that mistakes are made in a comprehensive diagnosis, as the physician cannot master all of this dramatically increasing volume of knowledge. The knowledge has extended beyond the memory of human beings, thereby causing the deterioration of service; this is called the "Knowledge crisis." To tackle this problem, the Electronic Medical Textbook (EMT) has been conceived and set up as a medical knowledge base for physicians to optimize both their specialties and activities in clinical practice. Meanwhile, laboratory information systems were widely introduced. However, there are few systems which allow interpretation of the findings obtained. With this in mind, we have improved the utility of the EMT by enhancing its function with laboratory information follow-up, thesaurus back-up, Japanese language support, and online access. 2. SYSTEM DESCRIPTION. The knowledge database for medical decision-making consists of three categories: 1) Medical domain knowledge (including approximately 3500 diseases) from the AMA's "The Current Medical Information & Terminology (CMIT)"; 2) Knowledge on relationship between laboratory testing results and diseases from "The Effects of Disease on Clinical Laboratory," compiled by the AACC; and 3) Clinical testing knowledge from Otsuka's laboratory test handbook "Kensa-Kojien." These categories are connected by links in the process of cross-reference. In actual use, the first is to select the supporting system bringing up clinical signs and findings on CRT from which users can then choose any representations corresponding to the patient's clinical state. Once the relevant objects have been selected, the system presents the correlated investigative tests to be performed, along with a scope of laboratory tests ordering for its initial investigative task. The required tests against the data objects denoted by "High," "Low," or "Abnormal" are linked to possible diagnoses, which appear on CRT in order of likelihood. Similarly, the possible diagnoses can be obtained directly by consulting the patient's laboratory test results in linkage, by way of automated data transformation into the corresponding data object using the reference interval. If necessary, additional information relative to clinical signs can be added. With the repetition of this procedure, clinically useful tests can be located, thus increasing the likelihood of an appropriate diagnosis. The proposed diseases can be confirmed through cross-reference to the patient's clinical signs from the description in the Textbook on CRT. In order to bolster the efficiency of cross-checking on CRT, the sentences including hit-words are highlighted in red. Moreover, with regard to specific keywords for disease, those sentences are highlighted in green to emphasize differences in between. In parallel, the description points out an active behavior of laboratory test results in the progression of the disease and is also able to display applicable laboratory test listings. Furthermore, this knowledge-based interpretation system is directly accessible via online network services in referring to laboratory test results. 3. CONCLUSION. A combination of the CMIT and laboratory diagnostic information in the knowledge database allows the narrowing down of proposed diagnoses due to its flexible approach, which depends not only on clinical signs and findings, but also on applicable test-ordering support and suggestions. This enhances the potential usefulness of the EMT. The system contributes to the support of the diagnostic procedures and assists in educational setting, because the process can be operated in reverse based on clinical signs and laboratory findings in a dialogue style on CRT. The related disease description highlighted in color has won a good reputation dur

Artificial Intelligence↗

Improved student learning in ophthalmology with computer-aided instruction.

PURPOSE: Recent changes in the medical school curriculum and in teaching styles have stimulated the development of novel learning resources. We investigated the impact of computer-aided learning in the field of ophthalmology at a large Australian undergraduate medical school. METHODS: Clinical case studies describing common ophthalmic conditions were incorporated into a computing program which uses a problem-solving format. The program was made available to 85 medical students for a 2 week period. A control group of 20 medical students did not have access to this material. Acquisition of new knowledge was assessed as the improvement in score on a knowledge-based multiple-choice examination which students took both before and following the learning interval. RESULTS: Students in the control group showed no improvement over the test period, whilst the students who had access to the computer significantly increased their knowledge base, both for material provided on the program (p = 0.0001) and in related areas (p = 0.0015). CONCLUSIONS: Suitably constructed material on the computer is a useful aid in teaching ophthalmology to medical undergraduates. The material and the medium may also act as a stimulus for further learning.

Computer-Assisted Instruction↗

Knowledge-engineering software. A demonstration of a high-end tool.

Many investigators wanting to apply knowledge-based systems (KBSs) as consultants for cancer diagnosis have turned to tools running on personal computers. While some of these tools serve well for small tasks, they lack the power available with such high-end KBS tools as KEE (Knowledge Engineering Environment) and ART (Automated Reasoning Tool). These tools were originally developed on Lisp machines and have the full functionality of the Lisp language as well as many additional features. They provide a rich and highly productive environment for the software developer. This paper illustrates the capability of one of these high-end tools. First, a table showing the classification of benign soft tissue tumors was converted into a KEE knowledge base. The tools available in KEE were then used to identify the tumor type for a hypothetical patient.

Age Factors↗

Fault diagnosis in an expert system for health services management in the tropics.

An integrated large-scale expert system called Health-2000, for the management of health services in regions where tropical diseases are endemic, has been designed. This system combines knowledge and databases, the contents of which are operated upon by an inference engine, to produce usable information. The system allows a host of applications, ranging from medical diagnosis to fault detection and preventive maintenance of biomedical equipment. The theoretical background and approach used in the development of the fault diagnosis and equipment maintenance sub-system of Health-2000 is presented. Model-based knowledge acquisition, and an extension of the Failure Modes, Effects and Criticality Analysis are two methodologies applied to build its knowledge bases. The inference engine which supports backward and forward chaining, operates on numerical and non-numerical facts, and uses fuzzy logic to handle vague and uncertain knowledge. Fault isolation proceeds in a top-down fashion, from equipment sub-system, to modules and components.

Developing Countries↗