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PubMed2001

Review of Expert System (ES), Geographic Information System (GIS), Decision Support System (DSS), and their applications in landfill design and management.

This paper provides the reader with a brief discussion on Expert System (ES), Geographic Information System (GIS), and Environmental Decision Support System (EDSS) technologies and their applications in environmental engineering in general and in landfill design and management in specific. It also brings into attention the benefits of integrating ESs and GISs together with simulation models (SM) in a decision support systems (DSS) framework to solve complex environmental problems, facilitated by the new advancements of computer technologies (both in hardware and software). Examples of such integration are provided to reflect how such a system can improve landfill design and management. Finally, the discussion concludes with the fact that although solving landfill design problems could greatly benefit from such a combination of technologies, there have been no attempts to combine ES, GIS, and SM for the comprehensive evaluation of landfill design and performance.

Decision Support Techniques↗
PubMed1993

Diagnostic tools for differentiating pleural mesothelioma from lung adenocarcinoma in paraffin embedded tissue. II. Design of an expert system and its application to the diagnosis of mesothelioma.

A panel of 14 antibodies (panepithelial antibody Lu-5, anti-keratin-18, anti-keratin-7, Ber-EP4, anti-Leu-M1, HEA-125, anti-carcinoembryonic antigen, anti-blood group-related antigens A, B, H, B72.3, anti-placental alkaline phosphatase, anti-vimentin and BMA-120), which have been evaluated for use in differentiating mesothelioma from lung adenocarcinoma, was applied to a group of 24 suspected mesotheliomas. Using the established qualitative, descriptive criteria derived from monovariate statistical analysis of the tumour control groups (definite mesotheliomas, adenocarcinomas), a definitive allocation was possible in only 25% of suspected cases. We therefore constructed two "expert systems", based on multivariate discriminant analysis with either the ALLOC 80 program for ordinal data or a newly developed analysis program for binomial data. With these two systems diagnostic allocation of suspected mesotheliomas was improved to 75% and 79%. The use of binomial data ("positive" versus "negative") in conjunction with the probability-based test system is of particular interest because the primary data are easy to record and the test results have a higher statistical probability.

Adenocarcinoma↗
PubMed1989

ESTER: an expert system for management of respiratory weaning therapy.

The withdrawal of mechanical ventilation generally presents no problems if carried out when the values of certain predictive physiological variables suggest that the patient will be able to breathe for him or herself. In certain cases, however, a more gradual weaning procedure is necessary, in which the amount of mechanical assistance provided is in some way reduced little by little. One of the usual means of achieving this gradual reduction is by intermittent mandatory ventilation (IMV), in which short bursts of mechanical ventilation are separated by progressively longer periods of "ventilator silence" which stimulate the patient's endogenous respiration. ESTER is an expert system in which the most widely accepted criteria are systematically called upon to supply advice to the clinician who has to prescribe a respiratory therapy regime suited to the needs of the patient. After effecting a preliminary prognosis of the patient's condition, ESTER asks for certain physiological parameters to be keyed in. Analysis of these parameters reveals the patient's condition and allows a recommended respiratory therapy to be designed.

Expert Systems↗
PubMed1990

The expert system approach to predicting protein structure.

Prediction of protein structure is an open-ended problem. Since an approach from first principles cannot be taken in reasonable computer time, short-cuts using further data are necessary. Such data include information about the specific protein in question, and information in databases which are about proteins in general. Is it possible to write a general, flexible 'superalgorithm' which would suit most circumstances? If so, it would seem likely to overcome one of the most understated but nonetheless greatest difficulties associated with molecular modelling and computer-aided drug design--reproducibility. To this end, a 'polymorphic programming environment' has been developed which represents both an expert system and a high-level language for theoretical chemists and molecular biologists. This language is GLOBAL (Ball et al., 1990). In a series of earlier studies, and more recently by means of GLOBAL itself, the nature of reproducibility and its rather surprising limits have been explored, and in general the current status and future potential of protein modelling have been examined.

Expert Systems↗
PubMed2003

In-silico screening of high production volume chemicals for mutagenicity using the MCASE QSAR expert system.

Computational screening is suggested as a way to set priorities for further testing of high production volume (HPV) chemicals for mutagenicity and other toxic endpoints. Results are presented for batch screening of 2484 HPV chemicals to predict their mutagenicity in Salmonella typhimurium (Ames test). The chemicals were tested against 15 databases for Salmonella strains TA100, TA1535, TA1537, TA97 and TA98, both with metabolic activation (using rat liver and hamster liver S9 mix test) and without metabolic activation. Of the 2484 chemicals, 1868 are predicted to be completely nonmutagenic in all of the 15 data modules and 39 chemicals were found to contain structural fragments outside the knowledge of the expert system and therefore suggested for further evaluation. The remaining 616 chemicals were found to contain different biophores (structural alerts) believed to be linked to mutagenicity. The chemicals were ranked indescending order according to their predicted mutagenic potential and the first 100 chemicals with highest mutagenicity scores are presented. The screening result offers hope that rapid and inexpensive computational methods can aid in prioritizing the testing of HPV chemicals, save time and animals and help to avoid needless expense.

Animals↗
PubMed1993

MultiMap: an expert system for automated genetic linkage mapping.

With the advent of the Human Genome Project, the ability to rapidly construct comprehensive and accurate linkage maps based on genetic marker data from family studies is an absolute necessity. In addition to their usefulness in localizing genes for both simple and complex disorders, linkage maps are invaluable tools for genetic counseling using linked marker genes. Several computer program packages are publicly available which aid in the construction of linkage maps by computing multipoint likelihoods for specified locus orders. However, these programs work in a step-by-step fashion, requiring intensive user-intervention and analysis at each step. Such a repetitive process is amenable to computerized automation. We have developed and tested an expert system computer program, MultiMap, for automated genetic linkage mapping. This program greatly reduces the amount of user-computer interaction, increasing the accuracy and speed with which a map can be constructed. In addition, because the total mapping time is greatly reduced through automation, it is now feasible to explore and compare various mapping heuristics and mapping criteria in order to develop the most appropriate approach, or set of approaches, for genetic linkage mapping. MultiMap need not be restricted to the construction of genetic maps, but could be adapted to aid in the automated construction of physical maps as well.

Automation↗
PubMed2006

W3MAMCAT: a world wide web based tool for mammillary and catenary compartmental modeling and expert system distinguishability.

W(3)MAMCAT is a new web-based and interactive system for building and quantifying the parameters or parameter ranges of n-compartment mammillary and catenary model structures, with input and output in the first compartment, from unstructured multiexponential (sum-of-n-exponentials) models. It handles unidentifiable as well as identifiable models and, as such, provides finite parameter interval solutions for unidentifiable models, whereas direct parameter search programs typically do not. It also tutorially develops the theory of model distinguishability for same order mammillary versus catenary models, as did its desktop application predecessor MAMCAT+. This includes expert system analysis for distinguishing mammillary from catenary structures, given input and output in similarly numbered compartments. W(3)MAMCAT provides for universal deployment via the internet and enhanced application error checking. It uses supported Microsoft technologies to form an extensible application framework for maintaining a stable and easily updatable application. Most important, anybody, anywhere, is welcome to access it using Internet Explorer 6.0 over the internet for their teaching or research needs. It is available on the Biocybernetics Laboratory website at UCLA: www.biocyb.cs.ucla.edu.

Algorithms↗
PubMed1997

The use of an expert system of composite risk factors in breast cancer screening.

Mass Screening seems to be the only promising way to discover breast cancer patients at an early and more curable stage and a positive method improving the cost-effectiveness and compliance of mass screening is the use of prognostic factors, to identify the high-risk group, who alone then would be screened. In a 200 women sample, who had undergone screening for breast cancer with clinical examination and bilateral mammography, we calculated the Composite Risk Factors of six Characteristics (C6RF), which are family history for breast cancer, pregnancy history, menstrual history, history of cystic breast disease, history of regular breast clinical or self-examination and presence or not of breast lump, using an expert system in IBM-compatible personal computer. In these cases the average C6RF was 0.18 (SD +/- 0.19) in low-risk group and 2.61 (SD +/- 4.76) in high-risk group and all cases with C6RF values higher than 0.56 were put in the high-risk group. Under these conditions, the sensitivity of the C6RF method, in discovering breast cancer, was 90% and the specificity 81.5% and the C6RF method was proved to be clinically valuable in identifying the high-risk group and controlling breast cancer.

Adult↗
PubMed2003

Comparative evaluation of the VITEK 2 Advanced Expert System (AES) in five UK hospitals.

OBJECTIVES: We carried out an evaluation of VITEK 2 in five UK laboratories, comparing results with 'gold standard' agar-dilution MIC data, assessing its ability to recognize resistant phenotypes and comparing results with those generated by routine antimicrobial susceptibility testing methods. METHODS: Laboratories tested a collection of 82 strains selected on the basis of their challenging and characterized resistance mechanisms. RESULTS: In comparison with the reference MIC method, VITEK 2 gave an essential agreement of 304/315 (enterococci), 1619/1674 (staphylococci) and 2937/3074 (Gram-negative bacilli): overall 96.0% agreement. Corresponding category (SIR) agreements with VITEK 2 were 247/252, 1496/1561 and 2478/2626 (overall 95.1%). Using five routine methodologies, category agreements ranged from 58/63 to 45/45; 222/232 to 174/174, and 333/372 to 250/259 for the three organism groups with an overall agreement of 95.0%. In contrast to VITEK 2 Advanced Expert System (AES), routine microbiology laboratories did not attempt to detect resistance mechanisms for every antibiotic studied. VITEK 2 AES detected all 19 resistance mechanisms in enterococci: where applicable, routine methods detected 14, 10 and 10. Of 30 resistance mechanisms in staphylococci, VITEK 2 AES detected 25 compared with 23, 20, 17 and 18 detected by routine methods. Finally, of 44 resistance mechanisms in Gram-negative bacilli, VITEK 2 AES detected 30 compared with 30, 23, 15 and 10 detected by routine methods. CONCLUSIONS: VITEK 2 performed susceptibility tests accurately and the AES detected and interpreted resistance mechanisms appropriately. Heavy inocula in a liquid medium possibly favour better expression of certain resistance determinants. Although certain routine microbiology methods performed adequately, VITEK 2 AES offers a rapid, standardized method suited to laboratories lacking experience of resistance mechanisms and/or those not testing an appropriate number, or range, of antibiotics to detect resistance phenotypes.

Bacteria↗
PubMed2005

Development of an expert system for classification of medical errors.

The 1999 report published by the Institute of Medicine (IOM) indicated that between 44,000 and 98,000 unnecessary deaths per year occurred in hospitals alone, as a result of errors committed by medical professionals in the United States. There has been considerable speculation that these figures are either overestimated or underestimated. For example, the possibility that they focus on isolated injuries rather than error, or the majority of surveyed respondents did not know what constitutes a (medical) error. These disagreements have led experts to challenge the estimates of patient harm attributable to error, as well as the methodologies used to enumerate them. Of particular concern is the process used in the identification, classification and prevention of medical errors. There have been numerous attempts to develop classifications of medical errors, and currently an abundance of taxonomies exist to describe their mechanism.In previous research, (Kopec, Kabir, Reinharth, Rothschild & Castiglione, 2003) a new taxonomy of Medical Errors was designed by expanding the IOM classification. This model and its extension can be used as a blueprint for future design, development and implementation of an expert system for classification of medical errors. Effective classification can facilitate pattern recognition, and pattern recognition will help in understanding the nature, background and abatement of medical errors. Such a system's goal will be to perform convincingly as an advisory consultant, exhibiting expertise on a par with and beyond human experts in specified domains. Despite substantial disagreement on the validity of the published figures for fatalities in hospitals in the IOM report, what is of importance is that the number of deaths caused by such errors is nonetheless alarming. The identification and classification of errors in medical care delivery is a very complex process, and this process can be facilitated and simplified by the implementation of an effective classification system.

Delivery of Health Care↗
PubMed2006

An artificial neural network-based expert system for the appraisal of two-car crash accidents.

This paper employs artificial neural network (ANN) to develop an accident appraisal expert system. Two ANN models-- party-based and case-based-- with different hidden neurons are trained and validated by k-fold (k=3) cross validation method. A total of 537 two-car crash accidents (1074 parties involved) are randomly and equally divided into three subsets. For the comparison, a discrimination analysis (DA) model is also calibrated. The results show that the ANN model can achieve a high correctness rate of 85.72% in training and 77.91% in validation and a low Schwarz's Bayesian information criterion (SBC) of -0.82 in training and 0.13 in validation, which indicates that the ANN model is suitable for accident appraisal. Furthermore, in order to measure the importance of each explanatory variable, a general influence (GI) index is computed based on the trained weights of ANN. It is found that the most influential variable is right-of-way, followed by location and alcoholic use. This finding concurs with the prior knowledge in accident appraisal. Thus, for the fair assessment of accident liabilities the correctness of these three key variables is of critical importance to police investigation reports.

Accidents, Traffic↗
PubMed1987

An expert system for oral diagnosis.

Although dentists are beginning to use computers in their offices for billing, insurance, and word processing, applications in computer-assisted diagnosis have not developed as rapidly. In medicine, use of computer-assisted techniques leads to more accurate and timely diagnoses and improves the quality of patient care through reduction in morbidity and increased physician interaction with patients. This article describes and discusses a system which, though developed for medical diagnosis, has very real applicability in dentistry. This PC-based, expert system takes variable input from the patient and links it with a large fixed database that is designed to deal with a specific patient problem. Output in the form of suggested causes and/or management options is delivered to the practitioner. Several modules have been developed and are ready for clinical use. The module "Periapical Radiolucency" will be described in this article to illustrate some of the characteristics of this system.

Diagnosis, Computer-Assisted↗
PubMed1987

Psyxpert: an expert system prototype for aiding psychiatrists in the diagnosis of psychotic disorders.

Psyxpert is an expert computer system prototype designed to aid psychiatrists in the diagnosis of mental disorders, in cases where psychotic features are the prominent part of the presenting clinical picture. The knowledge base contains psychiatric knowledge in the form of production rules. The system uses a backward-chaining control strategy to guide the consultation. Psyxpert provides a menu-driven user interface and an explanation subsystem. The system uses certainty and importance measures to produce a diagnosis with an attached certainty factor and recommendations for further evaluation or therapy. Psyxpert is written in Virginia Tech HC Prolog and runs on Digital Equipment Corporation's VAX 11/780 under the VMS operating system.

Computer Systems↗
PubMed2003

Evaluation of VITEK 2 for analysis of Enterobacteriaceae using the Advanced Expert System (AES) versus interpretive susceptibility guidelines used at Dynacare Kasper Medical Laboratories, Edmonton, Alberta.

OBJECTIVE: To evaluate the applicability and adaptability of the bioMérieux VITEK 2 Advanced Expert System (AES) to the customized interpretive susceptibility guidelines used at Dynacare Kasper Medical Laboratories (DKML). METHODS: Three hundred isolates of Enterobacteriaceae (not more than 30% Escherichia coli) were tested on the VITEK 2 system and the API 20E for identification. Susceptibility testing for these isolates was performed on the VITEK 2 system and the Pasco broth microdilution panels. Minimal inhibitory concentrations (MICs) and interpreted results according to the AES and DKML antimicrobial susceptibility guidelines were compared. RESULTS: Of 300 isolates tested for susceptibility, 13 did not give AES interpretations. Of the remaining 287 isolates, interpretations between AES and DKML guidelines were compared for 10 antibiotics. The overall correlation between the AES and DKML interpretations was 96.2%. CONCLUSION: This study demonstrated the benefits and limitations of the bioMérieux AES. Automated knowledge-based systems provide a useful laboratory tool for the interpretation of susceptibility results.

Alberta↗
PubMed2006

Electroencephalographic staging of hepatic encephalopathy by an artificial neural network and an expert system.

AIM OF THE STUDY: To provide an objective EEG assessment of hepatic encephalopathy (HE), we set up and tested an entirely automatic procedure based on an artificial neural network-expert system software (ANNESS). PATIENTS AND METHODS: A training set sample of 50 EEG (group A) and a test sample of 50 EEG (group B) of 100 cirrhotic patients were considered. The EEGs had been visually classified by an expert electroencephalographer, using a modified five-degree Parsons-Simith classification of HE. The efficiency of the ANNESS, trained in group A, was tested in group B. RESULTS: Both the ANNESS and the visually-based classifications were found to be correlated to liver insufficiency, as assessed by the Child-Pugh score (Spearman's coefficient rho=0.485, P<0.0001; rho=0.489, P<0.0001, respectively) and by the biochemical indexes of hepatic function (bilirubin: rho=0.31 vs. 0.27; albumin: rho=-0.13 vs. -0.18; prothrombin time rho=-0.35 vs. -0.52). The classifications were found to be correlated to each other (rho=0.84 P<0.0001, Cohen's kappa=0.55). However, the ANNESS overestimated grade 2 EEG alterations. CONCLUSION: An ANNESS-based classification of EEG in HE provided data comparable with a visually-based classification, except for mild alterations (class 2) that tended to be overestimated. Further optimization of automatic EEG staging of HE is desirable, as well as a prospective clinical evaluation.

Aged↗
PubMed2005

Evaluation and updating of the Osiris expert system for identification of Escherichia coli beta-lactam resistance phenotypes.

Osiris is a video zone size reader for disk diffusion tests that includes a built-in extended expert system (EES). We evaluated the efficacy of the Osiris EES for the identification of beta-lactam susceptibility phenotypes of Escherichia coli isolates. Fifteen beta-lactam agents and three beta-lactam-beta-lactamase inhibitor combinations were tested by the disk diffusion method against 50 E. coli strains with well-characterized resistance mechanisms. The strains were screened for the production of extended-spectrum beta-lactamase (ESBL) by the double-disk synergy test using a disk of amoxicillin-clavulanic acid with disks of the extended-spectrum cephalosporins and aztreonam. Overall, the EES accurately identified the phenotype for 78% of the strains, indicated an inexact phenotype for 17% of the strains, and could not find a matching phenotype for the remaining 5% of the strains. The percentage of correct identification for each resistance mechanism was 100% for inhibitor-resistant TEM and for TEM plus cephalosporinase, 88.9% for TEM and for ESBL, 70.8% for cephalosporinase overproduction, and 25% for oxacillinase. The main cause of discrepancy was the misidentification of oxacillinase as inhibitor-resistant TEM. The conventional double-disk synergy test failed to detect ESBL production in two strains (one producing VEB-1 and one producing CTX-M-14), but synergy between cefepime and amoxicillin-clavulanic acid was visible after the distance between the disks was reduced to 20 mm. After the interpretative guidelines of the EES were updated according to our results, the percentage of correct phenotype identification increased from 78 to 96%.

Anti-Bacterial Agents↗
PubMed2003

Evaluation of the Osiris expert system for identification of beta-lactam phenotypes in isolates of Pseudomonas aeruginosa.

Osiris is a video zone size reader for disk diffusion tests featuring a built-in extended expert system (EES). The efficacy of the EES for the identification of the beta-lactam susceptibility phenotypes of Pseudomonas aeruginosa isolates was evaluated. Thirteen beta-lactams were tested in four laboratories by the disk diffusion test with 53 strains with well-characterized resistance mechanisms, including the production of 12 extended-spectrum beta-lactamases (ESBLs). The plates were read with the Osiris system and the results were interpreted with the ESS, and then the phenotype identified by the EES was compared to the resistance mechanism. The strains were also screened for the presence of ESBL production by a double-disk synergy test by placing the strains between an extended-spectrum cephalosporin-containing disk and a clavulanic acid-containing disk at distances of 30, 20, 15, and 10 mm from each other. Overall, the EES accurately identified the phenotypes of 88.2% of the strains and indicated an association with several mechanisms for 3.8% of the strains. No phenotype was identified in four strains with low levels of penicillinase production. Misidentifications were observed for two penicillinase-producing strains: one strain with partially derepressed cephalosporinase production and one strain overexpressing the MexA-MexB-OprM efflux system. The production of only four ESBLs was detected by the standard synergy test with a 30-mm distance between the disks. The production of five further ESBLs was identified by reducing the distance to 20 mm, and the production of the last three ESBLs was detected only at a distance of 15 or 10 mm. Our results indicate that the Osiris EES is an effective tool for the identification of P. aeruginosa beta-lactam phenotypes. A specific double-disk synergy test with reduced disk distances is necessary for the detection of ESBL production by this organism.

Anti-Bacterial Agents↗