Multivariate analysis and expert systems.
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Chemistry, Clinical↗
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Results for “Expert Systems”
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Benefiting from expert systems.
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Expert Systems↗
Cluster randomised controlled trial of expert system based on the transtheoretical ("stages of change") model for smoking prevention and cessation in schools.
OBJECTIVES: To examine whether a year long programme based on the transtheoretical model of behaviour change, incorporating three sessions using an expert system computer program and three class lessons, could reduce the prevalence of teenage smoking. DESIGN: Cluster randomised trial comparing the intervention to a control group exposed only to health education as part of the English national curriculum. SETTING: 52 schools in the West Midlands region. PARTICIPANTS: 8352 students in year 9 (age 13-14 years) at those schools. MAIN OUTCOME MEASURES: Prevalence of teenage smoking 12 months after the start of the intervention. RESULTS: Of the 8352 students recruited, 7444 (89.1%) were followed up at 12 months. The intention to treat odds ratio for smoking in the intervention group relative to control was 1.08 (95% confidence interval 0.89 to 1.33). Sensitivity analysis for loss to follow up and adjustment for potential confounders did not alter these findings. CONCLUSIONS: The smoking prevention and cessation intervention based on the transtheoretical model, as delivered in this trial, is ineffective in schoolchildren aged 13-14.
Adolescent↗
Expert systems in laboratory medicine: a practical consultative application.
Today, more than ever, clinical pathologists will be required to act as consultants, while at the same time coping with ever-increasing workloads. We present a knowledge-based expert system for providing interpretive reports on over 100 specimens per day in a large commercial laboratory. The program's developmental history is reviewed, followed by a description of the program's structure and operation and how it is used and edited.
Diagnosis, Computer-Assisted↗
Multicentre evaluation of the VITEK 2 Advanced Expert System for interpretive reading of antimicrobial resistance tests.
Interpretive reading analyses the complete resistance profiles of bacteria to multiple antibiotics and infers the resistance mechanisms present; it aids therapeutic choice and enhances surveillance data. We evaluated the Advanced Expert System (AES), which interprets MICs generated by the VITEK 2. Ten European laboratories tested 42 reference strains and 76-106 of their own strains, representing important resistance genotypes. Interpretive reading by the VITEK 2 AES achieved full agreement with genotype data for 88-89% of strains, with the correct mechanism identified as one of two possibilities for a further 5-6%. Mechanisms inferred with 90% agreement with reference data included methicillin resistance in staphylococci, glycopeptide resistance in enterococci, quinolone resistance in staphylococci and Enterobacteriaceae, AAC(6')-APH(2")-mediated aminoglycoside resistance in Gram-positive cocci, erm-mediated macrolide resistance in pneumococci, extended-spectrum beta-lactamases (ESBLs) in Enterobacteriaceae and Pseudomonas aeruginosa, and acquired penicillinases in Enterobacteriaceae. VanA, VanB and VanC phenotypes of enterococci were distinguished reliably, and ESBL production was accurately inferred in AmpC-inducible species as well as Escherichia coli and Klebsiella spp. Mechanisms identified, but only as possibilities among several, included IRT-type beta-lactamases and individual aminoglycoside-modifying enzymes in Enterobacteriaceae. Most disagreements with reference data concerned pneumococci found to have high-level penicillin resistance by the VITEK 2 AES but previously determined, phenotypically, to have intermediate resistance. When ESBL production was inferred in E. coli and klebsiellae, the VITEK 2 AES edited susceptible results for cephalosporins (except cefoxitin) to resistant; when an acquired penicillinase was inferred in Enterobacteriaceae, piperacillin results were edited to resistant; and when staphylococci were found methicillin resistant, resistance was reported for all beta-lactams. Further editing may be desirable (e.g. of cephalosporin results for salmonellas inferred to have ESBLs).
Data Interpretation, Statistical↗
Utility of the VITEK 2 Advanced Expert System for identification of extended-spectrum beta-lactamase production in Enterobacter spp.
Forty clinical isolates of Enterobacter spp. were identified as extended-spectrum beta-lactamase (ESBL) producers by disk diffusion. The VITEK 2 Advanced Expert System (AES) identified the ESBL phenotype in only 25 isolates (62.5%), and erroneously reported cephalosporin susceptibility in 11 isolates (28%). Refinements in the AES are required in order to improve ESBL detection in Enterobacter.
Enterobacter↗
Networking and expert-system analysis: next frontier in biomonitoring.
The extensive use of biomarkers in environment biomonitoring programmes has raised the problem of data management and intercomparison. A research project (Pollution Effect Network, PEN) is proposed here, consisting of the realisation of an on-line warehouse for biomarker data (http://www.muf.unipmn.it/pen). The web site will contain repository sections and expert system procedures able to integrate information from different biomarkers and provide ranking of the organism health status in terms of synthetic stress syndrome indexes. Researchers accessing the site will be able to submit and process their own data. This will allow common criteria in the evaluation of the biological effects of pollutants, and an intercomparison of biomonitoring data among different geographic areas and sentinel species.
Animals↗
Avoiding digester imbalance through real-time expert system control of dilution rate.
Process control of anaerobic digesters is a particularly challenging problem because of the diversity of possible causes that can lead to digester imbalance. Conventional control schemes can fail in consequence of a reversal in the sign of the steady-state gain caused by some type of disturbance. In this work we present an expert system approach that takes into account the particularity of this process. The developed algorithm is demonstrated to compensate successfully for changes in the digester feed medium when simulated against a model for a continuous anaerobic digester.
Anaerobiosis↗
Design and application of an expert system for mobile phase optimisation in reversed-phase liquid chromatography.
The selection of the optimum composition for the mobile phase in reversed-phase high-performance liquid chromatography (HPLC) is a complex task; conventional approaches require the expenditure of significant amounts of time by the analyst, particularly for complex mixtures of solutes of biological origin. Some of the existing strategies for the automated optimisation of mobile phase composition (e.g. Simplex), may fail if the elution order of the components changes; or they may require that standards be chromatographed in order to establish the retention behaviour of each component in a mixture (e.g. resolution mapping). These problems may be overcome if the retention behaviour of each individual solute can be established from the chromatogram of the mixture. In this regard, components can be tracked by exploiting the spectral information generated by a rapid scanning photodiode array detector. Unfortunately this information is often insufficiently detailed to allow an unambiguous model of retention behaviour to be constructed. The system developed by the Authors uses these spectral data as a basis for constructing one or more hypothetical retention models, each of which is refined or rejected as further information is obtained during the progress of the experiment. To improve the reliability of the retention models proposed by the system, the spectral data are utilised in a number of tests designed to assess the purity of each chromatographic peak. The information so generated may be used in conjunction with any previously acquired spectral data both to select an appropriate method for extracting spectra for each component from the matrix of (A, lambda, t) data and to establish reliability parameters for the resultant spectra. The development and philosophy of the expert system developed for eluent optimisation in reversed-phase HPLC is discussed.
Journal Article↗
Expert systems for risk management.
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Expert Systems↗
Health and medical software related to computer user satisfaction: an interactive online expert system using diagnostic audit trails through telecommunication networks.
The selection of a health and medical software (HMS) system is a complicated process. The overall satisfaction derived from a system depends on many variables. This study analyzes the influence of HMS predictor variables on overall satisfaction as determined by multiple regression. The null hypothesis, that multiple correlation coefficient is zero, is rejected. Th alternative hypothesis is accepted. This study confirms the theories that suggest that HMS ease of operation, independent variables, technical support troubleshooting, and reliability of computer are the major determinations of overall computer user satisfaction. The factors identified were used in the design of an HMS expert system based on artificial intelligence (ESAI).
Computers↗
Diversity analysis of 14 156 molecules tested by the National Cancer Institute for anti-HIV activity using the quantitative structure-activity relational expert system MCASE.
Using the MCASE program, a procedure to analyze the diversity of the large amount of available HIV-1 antiviral data was proposed. A subset of 1 819 chemicals was logically selected from the original 14 156 chemicals tested by NCI. This subset of chemicals was shown to contain most of the structural and the functional information of the original database. A full analysis of the 1 819 chemicals by the MCASE program produced a correlation between chemical structures and HIV antiviral activity. In our model, 74 fragments were identified as being responsible for all the chemical's HIV antiviral activity. These fragments may be related to different inhibiting mechanisms, some known and some probably still unknown. The expert system resulting from this analysis can be used to predict the activity of new chemicals and to design new agents that can target multiple enzymes. This was shown to be the case by using the model to predict the activity of 10 diverse chemicals whose activities were not known at the time of model development. Of these, 8 were predicted in agreement with experimental observations. As far as we can tell, this is probably the first project ever to attempt to create a quantitative model of activity for such a massive database of diverse chemicals.
Anti-HIV Agents↗
Evaluation of a rule base for identifying contact allergens by using a regulatory database: Comparison of data on chemicals notified in the European Union with "structural alerts" used in the DEREK expert system.
To assess the suitability of the use of structural alerts to identify the skin-sensitising properties of chemicals, the 40 originally published structural alerts for the prediction of skin-sensitisation properties used by the DEREK system (which now contains 59 structural alerts), have been evaluated against a database developed in the German Federal Institute for Health Protection of Consumers and Veterinary Medicine (BgVV), which contains data submitted under the procedure for notifying new chemicals within the European Union. The evaluation of the 40 structural alerts used in DEREK revealed that eight of the 40 structural alerts for the prediction of skin-sensitising potential could be used without any further refinement. Ten structural alerts may need further specifications or refinements in order avoid false-positive predictions - proposals for refinement are discussed. Not enough substances were found within the BgVV database (containing data for more than 1000 substances) to evaluate ten of the DEREK substructures; hence, for these structural alerts, a judgement on their suitability for prediction of skin-sensitisation properties in expert systems is not possible. For 12 structural alerts, no comparative result could be obtained, because these rules did not "fire" for any of the examined chemicals. As a general result of the evaluation process, the approach of using structural alerts for the prediction of skin-sensitising properties of chemicals proved to be reliable. Proposals are given for a refinement of the structural alerts for prediction of contact allergy used in the DEREK system. In addition, advice and several preconditions are given, that apply when trying to teach a computer system to use structural alerts to predict toxicological properties.
Allergens↗
Development and prevalidation of a list of structure-activity relationship rules to be used in expert systems for prediction of the skin-sensitising properties of chemicals.
The new European Union (EU) chemicals policy, as described in the White Paper entitled Strategy for a Future Chemicals Policy, has identified a need for computer-based tools suitable for predicting the hazardous properties of chemicals. Two sets of structural alerts (fragments of chemical structure) for the prediction of skin sensitisation hazard classification ("R43, may cause sensitisation by skin contact") have been drawn up, based on sensitising chemicals from a regulatory database (containing data for the EU notification of new chemicals). These alerts comprise 15 rules for chemical structures deemed to be sensitising by direct action of the chemicals with cells or proteins within the skin, and three rules for substructures that act indirectly, i.e. requiring chemical or biochemical transformation. The predictivity rates of the rules were found to be good (positive predictivity, 88%; false-positive rate, 1%; specificity, 99%; negative predictivity, 74%; false-negative rate, 80%; sensitivity, 20%). Because of the confidential nature of the regulatory database, the rules are supported by examples of sensitising chemicals taken from the "Allergenliste" now held by the Federal Institute for Risk Assessment (BfR) and the DEREK for Windows expert system. The rules were prevalidated against data not used for their development. As a result of the prevalidation study, it is proposed that the two sets of structural alerts should be taken forward for formal validation, with a view to incorporating them into regulatory guidelines.
Animal Testing Alternatives↗
Development and validation of a computerized expert system for evaluation of automated visual fields from the Ischemic Optic Neuropathy Decompression Trial.
BACKGROUND: The objective of this report is to describe the methods used to develop and validate a computerized system to analyze Humphrey visual fields obtained from patients with non-arteritic anterior ischemic optic neuropathy (NAION) and enrolled in the Ischemic Optic Neuropathy Decompression Trial (IONDT). The IONDT was a multicenter study that included randomized and non-randomized patients with newly diagnosed NAION in the study eye. At baseline, randomized eyes had visual acuity of 20/64 or worse and non-randomized eyes had visual acuity of better than 20/64 or were associated with patients refusing randomization. Visual fields were measured before treatment using the Humphrey Field Analyzer with the 24-2 program, foveal threshold, and size III stimulus. METHODS: We used visual fields from 189 non-IONDT eyes with NAION to develop the computerized classification system. Six neuro-ophthalmologists ("expert panel") described definitions for visual field patterns defects using 19 visual fields representing a range of pattern defect types. The expert panel then used 120 visual fields, classified using these definitions, to refine the rules, generating revised definitions for 13 visual field pattern defects and 3 levels of severity. These definitions were incorporated into a rule-based computerized classification system run on Excel(R) software. The computerized classification system was used to categorize visual field defects for an additional 95 NAION visual fields, and the expert panel was asked to independently classify the new fields and subsequently whether they agreed with the computer classification. To account for test variability over time, we derived an adjustment factor from the pooled short term fluctuation. We examined change in defects with and without adjustment in visual fields of study participants who demonstrated a visual acuity decrease within 30 days of NAION onset (progressive NAION). RESULTS: Despite an agreed upon set of rules, there was not good agreement among the expert panel when their independent visual classifications were compared. A majority did concur with the computer classification for 91 of 95 visual fields. Remaining classification discrepancies could not be resolved without modifying existing definitions. Without using the adjustment factor, visual fields of 63.6% (14/22) patients with progressive NAION and no central defect, and all (7/7) patients with a paracentral defect, worsened within 30 days of NAION onset. After applying the adjustment factor, the visual fields of the same patients with no initial central defect and 5/7 of the patients with a paracentral defect were seen to worsen. CONCLUSION: The IONDT developed a rule-based computerized system that consistently defines pattern and severity of visual fields of NAION patients for use in a research setting.
Automation↗
Impact and management of confounding values and outliers in a neurotologic expert system.
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Central Nervous System↗
[Conflict between computerized expert systems: is there a pilot in the plane?].
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Bias↗