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PubMed2004

Knowledge base of clinicians regarding oral anticoagulant therapy in a teaching institution--a questionnaire survey.

AIMS: Maintaining international normalized ratios (INRs) within the therapeutic range for patients on oral anticoagulant therapy is a tough task. Physician practices have a vital bearing on safe management in these patients. We sought to assess the knowledge base of clinicians in our hospital regarding oral anticoagulant treatment. METHODS: A retrospective review of 3152 consecutive INRs in patients on outpatient oral anticoagulant treatment (OAT) was carried out over a 16 month period. To assess clinician practices, we performed a questionnaire survey (20 questions) on various aspects of OAT among 65 clinicians (response rate--89%). RESULTS: 76.3% of the INRs were in the sub-therapeutic range, 19.1% in the therapeutic range while 4.6% INRs were beyond therapeutic range. Fifty five completed questionnaires were returned by 24 consultants and 35 residents. Knowledge of clinicians regarding the loading dose of the oral anticoagulant, target INR range, the colour of the tablet was not adequate with 21, 28 and 23 correct responses respectively. Documentation of dietary and drug history was inadequate with 13 and 38 responses respectively. Patient education was limited to only verbal information to patients on anticoagulation. Most clinicians performed baseline screens before starting therapy. Although majority of clinicians (41) reported haemorrhagic complications in patients, just under one-third (28.8%) clinicians encountered thrombosis more often. Significant differences between the knowledge of consultants and residents was only found in responses for the correct loading dose (p < 0.0007) and the laboratory methodology in use for PT/INR determination (p < 0.04). CONCLUSIONS: Knowledge base of clinicians regarding oral anticoagulant management was unsatisfactory. A tendency to under-dose patients was observed. There is need for stricter adherence to accepted guidelines of anticoagulant therapy with particular emphasis on patient education.

Administration, Oral↗

PubMedDate not supplied

Knowledge-based interaction fingerprint scoring: a simple method for improving the effectiveness of fast scoring functions.

A new method for the postprocessing of docking outputs has been developed, based on encoding putative 3D binding modes (docking solutions) as ligand-protein interactions into simple bit strings, a method analogous to the structural interaction fingerprint. Instead of employing traditional scoring functions, the method uses a series of new, knowledge-based scores derived from the similarity of the bit strings for each docking solution to that of a known reference binding mode. A GOLD docking study was carried out using the Bissantz estrogen receptor antagonist set along with the new scoring method. Superior recovery rates, with up to 2-fold enrichments, were observed when the new knowledge-based scoring was compared to the GOLD fitness score. In addition, top ranking sets of molecules (actives and potential actives or decoys) were structurally diverse with low molecular weights and structural complexities. Principal component analysis and clustering of the fingerprints permits the easy separation of active from inactive binding modes and the visualization of diverse binding modes.

Cluster Analysis↗

PubMed2001

CASP2 knowledge-based approach to distant homology recognition and fold prediction in CASP4.

In 1996, in CASP2, we presented a semimanual approach to the prediction of protein structure that was aimed at the recognition of probable distant homology, where it existed, between a given target protein and a protein of known structure (Murzin and Bateman, Proteins 1997; Suppl 1:105-112). Central to our method was the knowledge of all known structural and probable evolutionary relationships among proteins of known structure classified in the SCOP database (Murzin et al., J Mol Biol 1995;247:536-540). It was demonstrated that a knowledge-based approach could compete successfully with the best computational methods of the time in the correct recognition of the target protein fold. Four years later, in CASP4, we have applied essentially the same knowledge-based approach to distant homology recognition, concentrating our effort on the improvement of the completeness and alignment accuracy of our models. The manifold increase of available sequence and structure data was to our advantage, as well as was the experience and expertise obtained through the classification of these data. In particular, we were able to model most of our predictions from several distantly related structures rather than from a single parent structure, and we could use more superfamily characteristic features for the refinement of our alignments. Our predictions for each of the attempted distant homology recognition targets ranked among the few top predictions for each of these targets, with the predictions for the hypothetical protein HI0065 (T0104) and the C-terminal domain of the ABC transporter MalK (T0121C) being particularly successful. We also have attempted the prediction of protein folds of some of the targets tentatively assigned to new superfamilies. The average quality of our fold predictions was far less than the quality of our distant homology recognition models, but for the two targets, chorismate lyase (T0086) and Appr>p cyclic phosphodiesterase (T0094), our predictions achieved the top ranking.

ATP-Binding Cassette Transporters↗

PubMedDate not supplied

Statistical modeling of a ligand knowledge base.

A range of different statistical models has been fitted to experimental data for the Tolman electronic parameter (TEP) based on a large set of calculated descriptors in a prototype ligand knowledge base (LKB) of phosphorus(III) donor ligands. The models have been fitted by ordinary least squares using subsets of descriptors, principal component regression, and partial least squares which use variables derived from the complete set of descriptors, least angle regression, and the least absolute shrinkage and selection operator. None of these methods is robust against outliers, so we also applied a robust estimation procedure to the linear regression model. Criteria for model evaluation and comparison have been discussed, highlighting the importance of resampling methods for assessing the robustness of models and the scope for making predictions in chemically intuitive models. For the ligands covered by this LKB, ordinary least squares models of descriptor subsets provide a good representation of the data, while partial least squares, principal component regression, and least angle regression models are less suitable for our dual aims of prediction and interpretation. A linear regression model with robustly fitted parameters achieves the best model performance over all classes of models fitted to TEP data, and the weightings assigned to ligands during the robust estimation procedure are chemically intuitive. The increased model complexity when compared to the ordinary least squares linear model is justified by the reduced influence of individual ligands on the model parameters and predictions of new ligands. Robust linear regression models therefore represent the best compromise for achieving statistical robustness in simple, chemically meaningful models.

Algorithms↗

PubMed1989

A knowledge-based system for data analysis and interpretation.

Traditionally, statistical packages are employed to derive or infer facts about a Universe of Discourse through data analysis and interpretation. It is analysis that serves to transform data into information. Statistical packages provide the users with relatively easy-to-use and powerful mechanics of data analysis, but up to now they do not provide much help with the design and strategies of the analysis. As such, there is a risk of misuse of these packages by statistically inexperienced users. We propose the use of knowledge-based interfaces to support this category of users in statistical evaluations. This paper discusses our experiences from the implementation of a knowledge-based system called MAXITAB. It provides guidance in the processes of data analysis and interpretation and has been programmed as an interface to the statistical package MINITAB.

Data Interpretation, Statistical↗

PubMed2006

HEARTFAID: A knowledge based platform of services for supporting medical-clinical management of heart failure within elderly population.

HEARTFAID is a research and development project aimed at devising, developing and validating an innovative knowledge based platform of services, able to improve early diagnosis and to make more effective the medical-clinical management of heart diseases within elderly population. Chronic Heart Failure is one of the most remarkable health problems for prevalence and morbidity, especially in the developed western countries, with a strong impact in terms of social and economic effects. All these aspects are typically emphasized within the elderly population, with very frequent hospital admissions and a significant increase of medical costs. Recent studies and experiences have demonstrated that accurate heart failure management programs, based on a suitable integration of inpatient and outpatient clinical procedures, might prevent and reduce hospital admissions, improving clinical status and reducing costs. HEARTFAID aims at defining efficient and effective health care delivery organization and management models for the "optimal" management of the care in the field of cardiovascular diseases. The HEARTFAID innovative computerized system will improve the processes of diagnosis, prognosis and therapy provision, providing the following services: * electronic health record for easy and ubiquitous access to heterogeneous patients data;* integrated services for healthcare professionals, including patient telemonitoring, signal and image processing, alert and alarm system;* clinical decision support in the heart failure domain, based on pattern recognition in historical data, knowledge discovery analysis and inferences on patients' clinical data.The formalization of the pre-existing clinical knowledge and the discovery of new elicited knowledge represent the core of the HEARTFAID platform.

Aged↗

PubMed1994

A knowledge-based system for the interpretation of flow cytometry data in leukemias and lymphomas.

Flow cytometry immunophenotyping and analysis of DNA ploidy and proliferative activity have become extremely helpful techniques for diagnosing and subclassifying hematopoietic cell populations in a modern, full-service hematopathology laboratory. The number of physicians with special training in the interpretation of these studies is limited. A knowledge-based computer system has been designed to aid in the interpretation of immunophenotyping and DNA flow cytometry results in hematopoietic disease. The system, known as "Professor Fidelio," is a heuristic classification system that reasons on the basis of defined diagnostic patterns. In this study, Fidelio was tested as a stand-alone system on 366 specimens from two large tertiary medical centers. Fidelio's interpretation was considered to be appropriate in all cases. In 300 of 366 (82%) specimens, the system's interpretation agreed with the diagnosis of record. Many of the disagreements could be traced to errors in the recording of the original diagnosis and minor differences in diagnostic criteria between Fidelio's knowledge base and the criteria in use at the medical centers. When used in a stand-alone mode, Fidelio's interpretation was less specific than the diagnosis of record in certain lymphoproliferative disorders that require morphologic information for subclassification. Professor Fidelio is one module in a workstation for the diagnostic hematology laboratory. This workstation is designed for interpretive reporting, education, and database functions for clinical research. Clinical and morphologic information are shared between Fidelio and the other modules for peripheral blood analysis, bone marrow morphology, and lymph node interpretation by means of a relational database. The system will be useful in hospitals that lack individuals specially trained in flow cytometry.(ABSTRACT TRUNCATED AT 250 WORDS)

Artificial Intelligence↗

PubMed2005

Quantitative evaluation of protein-DNA interactions using an optimized knowledge-based potential.

Computational evaluation of protein-DNA interaction is important for the identification of DNA-binding sites and genome annotation. It could validate the predicted binding motifs by sequence-based approaches through the calculation of the binding affinity between a protein and DNA. Such an evaluation should take into account structural information to deal with the complicated effects from DNA structural deformation, distance-dependent multi-body interactions and solvation contributions. In this paper, we present a knowledge-based potential built on interactions between protein residues and DNA tri-nucleotides. The potential, which explicitly considers the distance-dependent two-body, three-body and four-body interactions between protein residues and DNA nucleotides, has been optimized in terms of a Z-score. We have applied this knowledge-based potential to evaluate the binding affinities of zinc-finger protein-DNA complexes. The predicted binding affinities are in good agreement with the experimental data (with a correlation coefficient of 0.950). On a larger test set containing 48 protein-DNA complexes with known experimental binding free energies, our potential has achieved a high correlation coefficient of 0.800, when compared with the experimental data. We have also used this potential to identify binding motifs in DNA sequences of transcription factors (TF). The TFs in 79.4% of the known TF-DNA complexes have accurately found their native binding sequences from a large pool of DNA sequences. When tested in a genome-scale search for TF-binding motifs of the cyclic AMP regulatory protein (CRP) of Escherichia coli, this potential ranks all known binding motifs of CRP in the top 15% of all candidate sequences.

Base Sequence↗

PubMed1995

Knowledge-based medical image analysis and representation for integrating content definition with the radiological report.

Technology breakthroughs in high-speed, high-capacity, and high performance desk-top computers and workstations make the possibility of integrating multimedia medical data to better support clinical decision making, computer-aided education, and research not only attractive, but feasible. To systematically evaluate results from increasingly automated image segmentation it is necessary to correlate them with the expert judgments of radiologists and other clinical specialists interpreting the images. These are contained in increasingly computerized radiological reports and other related clinical records. But to make automated comparison feasible it is necessary to first ensure compatibility of the knowledge content of images with the descriptions contained in these records. Enough common vocabulary, language, and knowledge representation components must be represented on the computer, followed by automated extraction of image-content descriptions from the text, which can then be matched to the results of automated image segmentation. A knowledge-based approach to image segmentation is essential to obtain the structured image descriptions needed for matching against the expert's descriptions. We have developed a new approach to medical image analysis which helps generate such descriptions: a knowledge-based object-centered hierarchical planning method for automatically composing the image analysis processes. The problem-solving steps of specialists are represented at the knowledge level in terms of goals, tasks, and domain objects and concepts separately from the implementation level for specific representations of different image types, and generic analysis methods. This system can serve as a major functional component in incrementally building and updating a structured and integrated hybrid information system of patient data.(ABSTRACT TRUNCATED AT 250 WORDS)

Artificial Intelligence↗

PubMed2001

Knowledge-based system for structured examination, diagnosis and therapy in treatment of traumatised teeth.

Dental trauma in children and adolescents is a common problem, and the prevalence of these injuries has increased in the last 10-20 years. A dental injury should always be considered an emergency and, thus, be treated immediately to relieve pain, facilitate reduction of displaced teeth, reconstruct lost hard tissue, and improve prognosis. Rational therapy depends upon a correct diagnosis, which can be achieved with the aid of various examination techniques. It must be understood that an incomplete examination can lead to inaccurate diagnosis and less successful treatment. Good knowledge of traumatology and models of treatments can also reduce stress and anxiety for both the patient and the dental team. Knowledge-based Systems (KBS) are a practical implementation of Artificial Intelligence. In complex domains which humans find difficult to understand, KBS can assist in making decisions and can also add knowledge. The aim of this paper is to describe the structure of a knowledge-based system for structured examination, diagnosis and therapy for traumatised primary and permanent teeth. A commercially available program was used as developmental tool for the programming (XpertRule, Attar, London, UK). The paper presents a model for a computerised decision support system for traumatology.

Adolescent↗

PubMedDate not supplied

Knowledge-based systems, removable partial denture design and the development of RaPiD.

Knowledge-based systems (KBS), otherwise and formerly known as 'expert systems', are computer programs that contain a representation of knowledge that can be used to solve problems normally requiring human intelligence. This article discusses the contributions such systems can make to medicine and dentistry, indicates the range of existing dental KBSs and gives reasons why removable partial denture (RPD) design has attracted so much attention in this respect. A description is also given of the 'RaPiD' system for designing RPDs at the chairside.

Computer-Aided Design↗

PubMed1991

A multimedia Anatomy Browser incorporating a knowledge base and 3D images.

We describe a multimedia program for teaching anatomy. The program, called the Anatomy Browser, displays cross-sectional and topographical images, with outlines around structures and regions of interest. The user may point to these structures and retrieve text descriptions, view symbolic relationships between structures, or view spatial relationships by accessing 3-D graphics animations from videodiscs produced specifically for this program. The software also helps students exercise what they have learned by asking them to identify structures by name and location. The program is implemented in a client-server architecture, with the user interface residing on a Macintosh, while images, data, and a growing symbolic knowledge base of anatomy are stored on a fileserver. This architecture allows us to develop practical tutorial modules that are in current use, while at the same time developing the knowledge base that will lead to more intelligent tutorial systems.

Anatomy↗

PubMed1999

Correlation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipper.

The relationship between the unfolding pseudo free energies of reduced and detailed atomic models of the GCN4 leucine zipper is examined. Starting from the native crystal structure, a large number of conformations ranging from folded to unfolded were generated by all-atom molecular dynamics unfolding simulations in an aqueous environment at elevated temperatures. For the detailed atomic model, the pseudo free energies are obtained by combining the CHARMM all-atom potential with a solvation component from the generalized Born, surface accessibility, GB/SA, model. Reduced model energies were evaluated using a knowledge-based potential. Both energies are highly correlated. In addition, both show a good correlation with the root mean square deviation, RMSD, of the backbone from native. These results suggest that knowledge-based potentials are capable of describing at least some of the properties of the folded as well as the unfolded states of proteins, even though they are derived from a database of native protein structures. Since only conformations generated from an unfolding simulation are used, we cannot assess whether these potentials can discriminate the native conformation from the manifold of alternative, low-energy misfolded states. Nevertheless, these results also have significant implications for the development of a methodology for multiscale modeling of proteins that combines reduced and detailed atomic models.

DNA-Binding Proteins↗

PubMed1991

Structure-function relationships in the cysteine proteinases actinidin, papain and papaya proteinase omega. Three-dimensional structure of papaya proteinase omega deduced by knowledge-based modelling and active-centre characteristics determined by two-hydronic-state reactivity probe kinetics and kinetics of catalysis.

1. A model of the three-dimensional structure of papaya proteinase omega, the most basic cysteine proteinase component of the latex of papaya (Carica papaya), was built from its amino acid sequence and the two currently known high-resolution crystal structures of the homologous enzymes papain (EC 3.4.22.2) and actinidin (EC 3.4.22.14). The method used a knowledge-based approach incorporated in the COMPOSER suite of programs and refinement by using the interactive graphics program FRODO on an Evans and Sutherland PS 390 and by energy minimization using the GROMOS program library. 2. Functional similarities and differences between the three cysteine proteinases revealed by analysis of pH-dependent kinetics of the acylation process of the catalytic act and of the reactions of the enzyme catalytic sites with substrate-derived 2-pyridyl disulphides as two-hydronic-state reactivity probes are reported and discussed in terms of the knowledge-based model. 3. To facilitate analysis of complex pH-dependent kinetic data, a multitasking application program (SKETCHER) for parameter estimation by interactive manipulation of calculated curves and a simple method of writing down pH-dependent kinetic equations for reactions involving any number of reactive hydronic states by using information matrices were developed. 4. Papaya proteinase omega differs from the other two enzymes in the ionization characteristics of the common (Cys)-SH/(His)-Im+H catalytic-site system and of the other acid/base groups that modulate thiol reactivity towards substrate-derived inhibitors and the acylation process of the catalytic act. The most marked difference in the Cys/His system is that the pKa for the loss of the ion-pair state to form -S-/-Im is 8.1-8.3 for papaya proteinase omega, whereas it is 9.5 for both actinidin and papain. Papaya proteinase omega is similar to actinidin in that it lacks the second catalytically influential group with pKa approx. 4 present in papain and possesses a catalytically influential group with pKa 5.5-6.0. 5. Papaya proteinase omega occupies an intermediate position between actinidin and papain in the sensitivity with which hydrophobic interaction in the S2 subsite is transmitted to produce changes in transition-state geometry in the catalytic site, a fact that may be linked with differences in specificity in P2-S2 interaction exhibited by the three enzymes.(ABSTRACT TRUNCATED AT 400 WORDS)

Amino Acid Sequence↗

PubMed1995

A knowledge-based care protocol system for ICU.

There is a growing interest in using care maps in ICU. So far, the emphasis has been on developing the critical path, problem/outcome, and variance reporting for specific diagnoses. This paper presents a conceptual knowledge-based care protocol system design for the ICU. It is based on the manual care map currently in use for managing myocardial infarction in the ICU of the Sturgeon General Hospital in Alberta. The proposed design uses expert rules, object schemas, case-based reasoning, and quantitative models as sources of its knowledge. Also being developed is a decision model with explicit linkages for outcome-process-measure from the care map. The resulting system is intended as a bedside charting and decision-support tool for caregivers. Proposed usage includes charting by acknowledgment, generation of alerts, and critiques on variances/events recorded, recommendations for planned interventions, and comparison with historical cases. Currently, a prototype is being developed on a PC-based network with Visual Basic, Level-Expert Object, and xBase. A clinical trial is also planned to evaluate whether this knowledge-based care protocol can reduce the length of stay of patients with myocardial infarction in the ICU.

Alberta↗

PubMed2002

A knowledge-based cone-beam x-ray CT algorithm for dynamic volumetric cardiac imaging.

With the introduction of spiral/helical multislice CT, medical x-ray CT began a transition into cone-beam geometry. The higher speed, thinner slice, and wider coverage with multislice/cone-beam CT indicate a great potential for dynamic volumetric imaging, with cardiac CT studies being the primary example. Existing ECG-gated cardiac CT algorithms have achieved encouraging results, but they do not utilize any time-varying anatomical information of the heart, and need major improvements to meet critical clinical needs. In this paper, we develop a knowledge-based spiral/helical multislice/cone-beam CT approach for dynamic volumetric cardiac imaging. This approach assumes the relationship between the cardiac status and the ECG signal, such as the volume of the left ventricle as a function of the cardiac phase. Our knowledge-based cardiac CT algorithm is evaluated in numerical simulation and patient studies. In the patient studies, the cardiac status is estimated initially from ECG data and subsequently refined with reconstructed images. Our results demonstrate significant image quality improvements in cardiac CT studies, giving clearly better clarity of the chamber boundaries and vascular structures. In conclusion, this approach seems promising for practical cardiac CT screening and diagnosis.

Algorithms↗

PubMed1991

Knowledge-based system for the diagnosis and treatment of hypertension.

A knowledge-based system to assist the physician in the diagnosis and treatment of hypertension has been developed as the result of cooperation between the Department of Electronic Engineering of the University of Florence and the Interuniversity Centre of Clinical Chronobiology. The system input consists of the data recorded over a 24 h (or longer) period by monitoring (automatically or through self-measurements) the blood pressure of the subject undergoing the system analysis, and the associated anamnestic data. The process results in a report that states from which kind of hypertensive syndrome, if any, the subject is suffering and which anti-hypertensive therapy appears to be most suitable. The system consists of three modules: the first diagnoses hypertension by applying cluster analysis to a set of parameters derived from the principal components of the time series resulting from the subject's blood pressure monitoring; the other two classify hypertension and offer advice about the most advisable treatment, respectively, by using high-level data representation and processing. The knowledge embedded in the system is internally represented by means of frames and rules. This paper describes the structure of the system, illustrates the techniques that have been used for its development and discusses the results of its application.

Artificial Intelligence↗

PubMed1995

Initial experience of using a knowledge based system for monitoring immunization services in Papua New Guinea.

A knowledge based system (KBS) which helps health service managers to interpret immunization coverage rates was installed in two provinces of Papua New Guinea. It was assessed over a period of 4 months to determine whether it was a potentially useful management tool. One province used the system but did not adjust its activities significantly because it was meeting its targets for immunization. In the other province the KBS helped provincial managers to detect problems and respond to them. Consequently, improvements in performance indicators were detected. It is difficult to attribute the improvements entirely to the KBS but several actions were taken to strengthen immunization services and the KBS appeared to support these. It appears that interventions which make routinely collected data more understandable and readily usable by health service managers can lead to improvements in the delivery of health services.

Follow-Up Studies↗