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PubMed1997

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↗
PubMed2004

The internet-based knowledge acquisition and management method to construct large-scale distributed medical expert systems.

The Internet offers an unprecedented opportunity to construct powerful large-scale medical expert systems (MES). In these systems, a cost-effective medical knowledge acquisition (KA) and management scheme is highly desirable to handle the large quantities of, often conflicting, medical information collected from medical experts in different medical fields and from different geographical regions. In this paper, we demonstrate that a medical KA/management system can be built upon a three-tier distributed client/server architecture. The knowledge in the system is stored/managed in three knowledge bases. The maturity of the medical know-how controls the knowledge flow through these knowledge bases. In addition, to facilitate the knowledge representation and application in these knowledge bases as well as information retrieval across the Internet, an 8-digit numeric coding scheme with a weight value system is proposed. At present, a medical KA and management system based on the proposed method is being tested in clinics. Current results have showed that the method is a viable solution to construct, modify, and expand a distributed MES through the Internet.

Computer Systems↗
PubMed1994

Integration of quantitative and qualitative reasoning: an expert system for cardiosurgical patients.

In this work the possibility of building an expert system to reason on the status of post-operative cardiac patients in intensive care units is analysed. The long-term knowledge consists of causal network which describes the main relationships between hemodynamic and metabolic quantities involved in the evolution after cardiac surgery. The inference engine uses an original hybrid formalism, which integrates numerical simulation and qualitative methods. If available, the numerical values of quantities and their exact mathematical relationships are employed; otherwise, the inference engine reasons by using a discrete qualitative representation of quantities. Simulations performed using real data indicate that integration of quantitative and qualitative methods reduces the number of diagnostic scenarios compatible with patient data, and constitutes a valid tool for reasoning about physiological disorders in terms of deep causal knowledge.

Atrial Function, Right↗
PubMed1997

[Comparative study of an expert system application in the prescription of medications].

BACKGROUND: The aim of this study was to evaluate the impact of a expert drug system implementation on the drug prescription habits and on drug cost in an university hospital. MATERIAL AND METHODS: During a 3 months period, the drug prescriptions to patients admitted to the Internal medicine, lung, gastroenterology and hepatology units, have been evaluated through the expert drug system (Medisource). This expert drug system functions in according to patients characteristics such as age, weight, height, sex, renal function and liver function. It recommends the correct dose, detects interactions and adverse effects and makes suggestions in pregnancy and lactation. It also offers alternative drugs with their cost. During the study period physicians were unaware of the investigation being performed. RESULTS: 836 patients (63.9 +/- 16.5 years) with an average hospital stay length of 11.6 +/- 6.7 days were studied. The most common diagnoses were: lung obstructive chronic disease, cirrhosis, gastrointestinal hemorrhage and cancer. The total amount of drug prescribed was 6,308. The expert system detected 458 overdosages and 33 underdosages, mainly in antibiotics and antiulcer drugs, and 1,722 interactions. The drug costs reduction that could be obtained following the expert system recommendations was 4.5% in antibiotic drugs and 23% in antiulcer drugs. CONCLUSION: The frequency of drug overdosage and underdosage in patients admitted in an university hospital is relatively high. The expert systems available for drug decisions could solve this problem.

Aged↗
PubMed1999

[Expert systems and automatic diagnostic systems in histopathology--a review].

In this decade, the pathological information system has gradually been settled in many hospitals in Japan. Pathological reports and images are now digitized and managed in the database, and are referred by clinicians at the peripherals. Tele-pathology is also developing; and its users are increasing. However, in many occasions, the problem solving in diagnostic pathology is completely dependent on the solo-pathologist. Considering the need for timely and efficient supports to the solo-pathologist, I reviewed the papers on the knowledge-based interactive expert systems. The interpretations of the histopathological images are dependent on the pathologist, and these expert systems have been evaluated as "educational". With the view of the success in the cytological screening, the development of "image-analysis-based" automatic "histopathological image" classifier has been on ongoing challenges. Our 3 years experience of the development of the pathological image classifier using the artificial neural networks technology is briefly presented. This classifier provides us a "fitting rate" for the individual diagnostic pattern of the breast tumors, such as "fibroadenoma pattern". The diagnosis assisting system with computer technology should provide pathologists, especially solo-pathologists, a useful tool for the quality assurance and improvement of pathological diagnosis.

Expert Systems↗
PubMed1988

[An expert system as an aid to the validation of results of the antibiogram. Feasibility study based on the example of Staphylococcus aureus].

A model of expert system using Prolog language was developed, to verify the coherence of the results of the antibiotic sensitivity test. Biological knowledge was formalized in three different ways: a credibility coefficient based on epidemiological data is assigned to known observed resistance; co-existent resistances are described with lists of "implicit" resistances, reflecting phenotypes commonly observed within some antibiotic groups; every single or "implicit" resistance is connected to a "gregarius" status, expressing the plasmidic nature of resistance. Applied to Staphylococcus aureus, the expert system is able to detect the inconsistencies of the antibiotic sensitivity test and to identify required knowledges. It therefore allows phenotypic interpretation of results.

Anti-Bacterial Agents↗
PubMed1994

An expert system for the interpretation of flow cytometric immunophenotyping data.

The development of high-grade non-Hodgkin's lymphomas in HIV-positive patients and patients with acquired immune deficiency syndrome (AIDS) is a well known phenomenon. The proper classification of these neoplasms often requires a multiparameter approach, including the interpretation of a large panel of immunologic markers analyzed by flow cytometry. The availability of individuals with the required expertise to properly interpret these marker studies is limited. For this reason, we have designed an expert system to automate the analysis of immunophenotyping panels in both HIV-related and non-HIV-related hematopoietic neoplasms. The expert system, which we call "Professor Fidelio", runs on IBM-compatible computers under Windows 3.0. The system is designed to accept any number of markers studied from a repertoire of 35 markers. Professor Fidelio functions on the basis of heuristic classification of defined diagnostic patterns. Nine specific patterns (Stem Cell, Myeloid and/or Monocytic, Erythroid, Megakaryocytic, Immature B-cell, Immature T-cell, Mature B-cell, Mature T-cell, and Plasma cell) and one "non-specific" pattern have been agreed upon. Fidelio's knowledge base contains the definitions of each of these patterns and the heuristics for excluding patterns when an incomplete panel of markers is performed. The inference engine interprets the findings (including the age of the patient) and reports the patterns which are matched, the differential diagnosis, the suggested diagnosis from the list of differentials if the marker studies are specific, and recommendations for additional tests which may be valuable in establishing the diagnosis.(ABSTRACT TRUNCATED AT 250 WORDS)

Acquired Immunodeficiency Syndrome↗
PubMedDate not supplied

Methodology for a medical expert system on fuzzy analog ganglionar lattices. Non-approximate reasoning with multiple antecendents of different relative importance and limited uncertainty.

This work presents an Expert System based on fuzzy analog ganglionar lattices. Its reasoning scheme is designed analogously to the expert's mental organization and it is realized on an (analog) operator called the ganglionar lattice. It is a connectionist system that uses the medical knowledge to define its architecture. The operator evokes some similarities to higher order neural networks and performs as the knowledge base and inference engine of the expert system, in a unified manner. A main feature of this operator is that it exhibits the variables corresponding to all intermediate concepts identified by the expert; this characteristic is shown to be most valuable for assessing, explicating and prospecting in medical applications. Further, it is capable of (i) evaluating a consequent for a variety of non-approximate reasonings with multiple antecendents of different relative importance under limited uncertainty; (ii) explicating the conclusions at different levels of abstraction to suit the user; and (iii) prospecting for the best 'a priori' sequence of unevaluated antecedents, from which to choose following tests. These procedures are based on the objective criterion of the consequent's uncertainty decrease (entropy). All results are produced in numerical form and may be translated into restricted natural language. A simple example of this technology is fully developed. Finally the method's potentials are discussed for future applications.

Artificial Intelligence↗
PubMedDate not supplied

Development of an exercise expert system for older adults.

The purpose of this study was to develop a computerized exercise expert system (CEES) that creates tailored exercise plans for older adults. A panel of experts was selected in the areas of medicine, exercise physiology, health promotion, exercise psychology, and gerontology. The experts communicated with the principal investigator and the project members by mail, email, telephone, and expert meetings. A two-day workshop was held during the second year for the project members as well as local and national experts to review the CEES. The CEES demonstrated adequate inter-rater reliability (0.80) and criterion validity (0.70). Content validity was achieved by literature review and expert opinion. The CEES gathers information on the elder's health status, clinical factors, and exercise determinants that characterize specific barriers or incentives to exercise. The software program then develops individualized exercise prescriptions that are customized to older adults.

Adult↗
PubMed2005

Phenotypic detection of beta-lactamase-mediated resistance to oxyimino-cephalosporins in Enterobacteriaceae: evaluation of the Mastascan Elite Expert System.

OBJECTIVES: The aim of this study was to evaluate phenotypic detection of beta-lactamase-mediated resistance to oxyimino-cephalosporins in Enterobacteriaceae using the Mastascan Elite Expert System challenged with a battery of genotypically characterized organisms. METHODS: Isolates (n = 120) were identified to species level and antimicrobial susceptibilities were determined using agar incorporation methods and Mastascan Elite. Phenotypes were examined using an Expert System (ES) and putative genotypes were suggested using interpretative reading. RESULTS: Identification was correct in 119 of 120 isolates. The ES was able to identify the correct beta-lactam phenotype (as deduced from molecular methods) in a single choice in 98 of 120 (81.7%) isolates. In an additional 15 (12.5%) cases, the ES identified the correct beta-lactam phenotype within two or more choices. The detected phenotype was incorrect in seven (5.8%) isolates, but three of these were not inherent to the ES. CONCLUSIONS: The Mastascan Elite ES is relatively inexpensive and flexible and can identify the mechanism of resistance to oxyimino-cephalosporins in the majority of Enterobacteriaceae without recourse to molecular methods.

Cephalosporins↗
PubMed1992

DIMSUM: an expert system for multiexponential model discrimination.

DIMSUM is a highly automated, rule-based expert system designed to fit multiexponential models of increasing dimension to time series data, followed by selection of the best candidate model based on a user-modifiable and weighted decision tree of statistical criteria for model discrimination. The major features of DIMSUM are 1) an interactive and friendly user interface; 2) options for incorporating prior information about the parameters, the data, and/or the system from which the data were collected, in the form of equality and inequality constraints; 3) a built-in algorithm for automatically obtaining starting values for parameter estimation; 4) a robust weighted least-squares parameter estimation algorithm operating in an adaptive, user-adjustable search space; 5) comprehensive statistical results comparing different order candidate models fitted to the data; and 6) a novel, user-modifiable (learning) rule-based advisory subsystem providing an "expert's" interpretation of these statistical results and an explanation of all advice.

Algorithms↗
PubMed1993

Specification of models in large expert systems based on causal probabilistic networks.

Problems involved in the specification of large expert systems are discussed. In the specification of causal probabilistic networks conditional probability tables for all nodes have to be provided. These conditional probability tables can often be described by models that specify the nature of interaction between nodes. Various types of models are described and a program that handles such models is presented. Large causal probabilistic networks often contain several copies of identical tables or structures. A header facility that provides common definitions of such repeated elements is proposed. This facility makes specifications much shorter and easier to construct and maintain.

Expert Systems↗
PubMed1997

XBONE: a hybrid expert system for supporting diagnosis of bone diseases.

In this paper, XBONE, a hybrid medical expert system that supports diagnosis of bone diseases is presented. Diagnosis is based on various patient data and is performed in two stages. In the early stage, diagnosis is based on demographic and clinical data of the patient, whereas in the late stage it is mainly based on nuclear medicine image data. Knowledge is represented via an integrated formalism that combines production rules and the Adaline artificial neural unit. Each condition of a rule is assigned a number, called its significance factor, representing its significance in drawing the conclusion of the rule. This results in better representation, reduction of the knowledge base size and gives the system learning capabilities.

Bone Diseases↗
PubMed2004

A diagnostic expert system for structured reports, quality assessment, and training of residents in sonography.

BACKGROUND: The quality of medical reports on diagnostic procedures has a considerable impact on the quality of medical care. Handwritten or otherwise unstructured reports tend to be incomplete, whereas structured questionnaires are of limited flexibility and not considered case-adequate. Thus, medical reports of this kind may promote an incomplete and misleading documentation and, therefore, be problematic with respect to their reliability. METHODS: SonoConsult (SC), an expert system for structured and case-adequate documentation of sonographic findings with an additional diagnostic component, was evaluated with respect to user acceptance and suitability for enhancing the quality of reports and supporting sonographic beginners. The expectations and the attitudes of the users toward the program were evaluated by anonymous questionnaires. The documentation of findings and the diagnostic conclusions in 103 free text reports made by experienced examiners were evaluated by subjecting their information to a subsequent input into SC. Free text reports were checked for information that was asked by SC but not mentioned in the reports. In a series of 150 cases, the system diagnoses were blinded during input of findings into SC-questionnaires and the examiners' diagnostic conclusions were compared with the uncovered SC-diagnoses with respect to forgotten diagnoses. RESULTS: The structured and data-driven acquisition of information by the program was well accepted by the users. However, only a medium interest in the system-delivered diagnoses was noted. The program-generated reports were characterized by a more detailed description of the findings and a higher number of diagnoses in comparison to the unstructured reports before introduction of SC as the only documentation system. When unaware of the system diagnoses, information was entered into the questionnaires, and SC generated some diagnoses which were not mentioned by the examiners in their conclusions. The possibility to inspect the system diagnoses led to an enhancement of the number of diagnoses the examiners mentioned in their conclusions. By contrast, the examiners meant that the influence of the program on their conclusions was minimal or dispensable. Beginners in sonography acknowledged that the program led them to perform a complete examination in an adequate sequence. CONCLUSION: An expert system for the data-driven, case-adequate information acquisition of abdominal ultrasound examinations may enhance the quality of the reports and, potentially, of the examinations at the same time. In addition, it may help beginners to learn a structured problem- and finding-adequate examination sequence.

Abdomen↗
PubMed1996

An expert system for the detection of cervical cancer cells using knowledge-based image analyzer.

Analyzing for abnormalities of cell images in the cervix uteri provides a basis for reducing deaths and morbidity from cervical cancer through detection of potentially cancerous cells, provision of prompt advice and opportunities for follow-up and treatments. However, cytopathology is usually based on subjective interpretation of morphological features. Arbitrary criteria have to be devised for their classifications. Subjective interpretations of such criteria are likely to result in diagnostic shifts and consequently disagreement occurs between different interpreters. This article presents a novel approach to the composition of segmentation and diagnosis processes for biomedical image analysis. A prototype expert system has been developed to provide an objective and reliable tool to gynaecologists. Special image analyzing techniques are used and a set of knowledge sources is designed. The expert system employs a robust control strategy which minimizes the amount of domain-specific control knowledge. It has been proved to work effectively in the detection of cervical cancer.

Artificial Intelligence↗
PubMed1995

Traditional Chinese medicine (TCM) expert system in postpartum nursing.

The method of TCM treatment is highly appreciated by Chinese people, because it is safe, without side effects, widely applicable, gives good results, and uses natural medicinal herbs. It is an ideal natural cure that will make contributions to the health of patients all over the world. The superiority of TCM nursing and treatment should be brought into full play--it is an active nursing method which deserves recommendation for postpartum nursing. This paper introduces the TCM expert system in postpartum nursing and discusses the features of TCM treatment and nursing by using concepts of modern cybernetics. The human body can be considered a high-level automatic control system in which there are many transinformation mediums, for example, neuro-system, humoral-system, meridian system (the response along the channels during acupuncture) etc. They stem from the very long process of evolution. Through the action of them, the body can adapt environments; keep normal metabolism and immunity; and possess the functions of compensation , learning, and self-repair, for example, conditioned reflexes, vaccination, etc. In general, the balancing tendency of dynamic body stays normal homeostate. If the body is ill, then its dynamic balancing tendency will be changed. TCM doctors can make use of remedy, acupuncture, and massage, etc. to regulate the balancing tendency of dynamic body to induce the defending ability itself and recover normal homeostate of body. The TCM nursing expert system in postpartum nursing has been finished. Its working environment must be CCDOS or UCDOS edition 3.0 and above. The hardware environment is PC/286, 386, or 486.

Expert Systems↗
PubMed1991

The initial use of a computer-controlled expert system in the treatment planning of Class II division 1 malocclusion.

A computer based expert system for providing orthodontic advice for Class II Division 1 malocclusion has been developed and evaluated. Treatment plans produced by the system for 31 non-prior approval cases drawn from material provided by the Dental Practice Board were compared with the treatments actually carried out by the practitioners. The shortcomings of the system are discussed.

Decision Trees↗