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Results for “Expert Systems”

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PubMed1997

[Expert systems in risk assessment. Risk or opportunity?].

Experts underwriting systems in the risk selection of individual life insurance have a high place value and are, in future, indispensable in the daily underwriting process. The chance to reduce drastically dual operations enables the insurance companies to make more cost-efficient underwriting decisions. The rapidly advancing technology develops not only new dimensions for individualism and for providing customer service but also for a fast underwriting process which is of great benefit to the insurers who are up against stiff competition. The qualified underwriter and the physician will be relieved of standard work and have more time in investing their knowledge and know-how in the underwriting process which calls for an absolutely individual reflection. New activities are inevitably ahead of this group of persons: Maintenance and attendance of the experts system! A task with which the quality of such a system stands and falls. We are expectant to see what the future has in store for this field.

Artificial Intelligence↗

PubMed1993

Connectionist expert systems as medical decision aid.

In this paper neural networks are used as associative memories to build an expert system for aiding medical diagnosis. As in expert systems using symbolic manipulation, the knowledge is introduced by a knowledge engineer using a collection of known cases. The system has an object-oriented approach to knowledge organization and the resulting network topology. Fuzzy sets are used to interpret connection values and/or excitation state of the units. The main result is that the proposed neural network allows not only finding a solution in some cases, but also suggests obtaining more clinical data if the data available is insufficient to reach a conclusion. This approach is illustrated by examples.

Adult↗

PubMed2002

[Expert systems as the instrument for postop diseases].

There was proposed an expert system for conduction of differential diagnosis of surgical diseases, stimulating the mathematic models creation, the filling up of tables of the features values of all diagnostic hypothesis possible with subsequent staged exception of the least adequate of them. The expert diagnostic system proposed may be applied in clinical practice and pedagogic process while teaching of students.

Expert Systems↗

PubMed1994

SETH: an expert system for the management on acute drug poisoning in adults.

The aim of SETH is to give end-users specific advice concerning treatment and monitoring of adult drug poisoning. SETH is developed with an off the shelf expert system shell (KBMS) and runs on a microcomputer. Technical choices were done according to this analysis, financial considerations and portability. Currently, the database contains 1000 French drugs from 75 different toxicological classes. The SETH expert system simulates the expert reasoning, taking into account for each toxicological class delay, signs and dose. Two phases of evaluation were performed. The experimental implementation of Seth began in April 1992 in our Poison Control Centre. Since then, 1100 cases inputted by residents were analysed by SETH. The extension of the knowledge base to child poisoning began in March 1993.

Acute Disease↗

PubMed1994

An expert system for teaching cytopathologic diagnosis of lung cancers.

An expert system for teaching cytopathologic skills is described. It uses Tao's cytologic criteria as graded feature parameters for comparison against a set of expert descriptors of known carcinomas. The system scores each diagnosis according to the degree of agreement along each feature axis. The system also allows the user to compare his/her description with that of the expert for any of the tumor entities. The expert knowledge base is abstracted into a numerical matrix within the system. This matrix is used for parameter comparison and score interpretation. This design is simple and compact, allowing portability and broad compatibility for small personal computers. Although testing is only at the initial stages, preliminary studies have shown that the system provides reproducible, consistent results. It is useful as a teaching tool for students, residents and staff pathologists.

Cell Biology↗

PubMed2006

Efficacy of a transtheoretical model-based expert system for antihypertensive adherence.

Blood pressure is not controlled in as many as 50%-75% of hypertensive patients, primarily because of inadequate adherence to treatment. This paper examines the efficacy of a Transtheoretical Model (TTM)-based expert system intervention designed to improve adherence with antihypertensives in a sample of 1,227 adults. Participants were proactively recruited and randomly assigned to receive usual care or three individualized expert system reports and a stage-matched manual over 6 months. Participants were surveyed at baseline, and 6, 12, and 18 months. Significantly more of the intervention group participants reported being in Action and Maintenance at follow-up time points (ie, 73.1% of the treatment group versus 57.6% of the control group at 12 months and 69.1% of the treatment group versus 59.2% of the control group at 18 months). Scores on a behavioral measure of nonadherence differed significantly at follow-up time points. TTM-based expert system interventions have the potential for a significant impact on entire populations of individuals who fail to adhere, regardless of their readiness to change.

Adult↗

PubMed1992

Development of an expert system advisor for anaesthetic control.

A review is given of numerous approaches which have been taken to provide automated control of depth of anaesthesia. Most of these approaches use a single indicator for anaesthetic state, and do not perform adequately for such a complex system. It is desirable, therefore, to merge a number of qualitative clinical signs and quantitative on-line measurements to provide decision-support for control of anaesthetic depth. The paper describes such an expert system called Resac (Real time Expert System for Advice and Control). Details of the knowledge representation and inference structure are given, together with the method adopted for propagating uncertainty measures, combining fuzzy information and merging quantitative and qualitative indicators. The importance of good human machine interface design is shown via the GEM-based graphics of Resac.

Anesthesiology↗

PubMed2001

Adaptive frequency decomposition of EEG with subsequent expert system analysis.

We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG.

Adolescent↗

PubMed1993

Graphical access to medical expert systems: IV. Experiments to determine the role of spoken input.

The goal of our research is to design improved interfaces for medical expert systems. Previously, the use of graphical techniques was explored to improve the acceptance by clinicians of the user interface. Now that devices that accept spoken input are available, we wish to design interfaces that take advantage of this potentially more natural modality for interaction. To understand how clinicians might want to speak to a medical decision-support system, we carried out an experiment that simulated the availability of a spoken interface to the ONCOCIN medical expert system. ONCOCIN provides therapy advice for patients on complex cancer therapy protocols based on a description of the patient's current medical status and laboratory-test values. In the experiment, we had oncologists present a clinical case while observing the ONCOCIN flowsheet display. A project member listened to the presentation and filled in values for the flowsheet, as well as introducing purposeful misunderstandings of the input. The results suggest that each individual developed a stereotypical grammar for communicating with the program. Our experience with the purposeful miscommunications suggests particular ways to tailor requests for repetition based on the part of the utterance that was not understood.

Decision Making, Computer-Assisted↗

PubMed1998

Expert system for control of anaerobic digesters.

Continuous anaerobic digesters are systems that present challenging control problems including the possibility that an unmeasured disturbance can change the sign of the steady-state process gain. An expert system is developed that recognizes changes in the sign of process gain and implements appropriate control laws. The sole on-line measured variable is the methane production rate, and the manipulated input is the dilution rate. The expert system changes the dilution rate according to one of four possible strategies: a constrained conventional set-point control law, a constant yield control law (CYCL) that is nearly optimal for the most common cause of change in the sign of the process gain, batch operation, or constant dilution rate. The algorithm uses a t test for determining when to switch to the CYCL and returns to the conventional set-point control law with bumpless transfer. The expert system has proved successful in several experimental tests: severe overload; mild, moderate, and severe underload; and addition of phenol in low and high levels. Phenol is an inhibitor that in high concentrations changes the sign of the process gain.

Acetates↗

PubMed1991

PREOP: development of an evidence-based expert system to assist with preoperative assessments.

PREOP is a prototype expert system that is designed to provide physicians with evidence-based recommendations concerning the assessment and care of patients with comorbid medical problems who are about to undergo surgery. The knowledgebase for this system is currently undergoing transition from the conventional advice of medical experts, which is variably related to evidence published in the medical literature, to a more formal approach in which the best available evidence is used for each recommendation and the quality of the evidence made apparent to the user. This work seeks to address important questions concerning improvement of the information contained in expert knowledgebases, namely, how to find and recognize new evidence when it is published, how to assess the quality of evidence in a uniform and efficient fashion, how to replace evidence in the knowledgebase efficiently when it has been superseded by higher quality evidence, and how to represent evidence in a manner that is most valuable for the user.

Decision Making, Computer-Assisted↗

PubMed1998

Detection of epileptiform activities in the EEG using neural network and expert system.

This paper proposes a multichannel spike detection in long term EEG monitoring for epilepsy. It is achieved by wavelet transform(WT), artificial neural network(ANN) and the expert system. First, a small set of wavelet coefficients is used to represent the characteristics of a single channel epileptic spikes and normal activities. The purpose of this WT is to reduce the number of inputs to the ANN. Next, three layer feed-forward network employing the error back propagation algorithm is trained and tested using parameters obtained by the WT. Spikes are identified in individual EEG channels by 16 identical neural networks. Finally, 16-channel expert system based on the context information of adjacent channels is introduced to reject artifacts and produce reliable results. In this study, epileptic spikes and normal activities were selected from 32 patient's EEGs (the seizure disorder: 12, normal: 20) in consensus among experts. The result shows that the WT reduced data input size and the preprocessed ANN had 97% sensitivity and 89.5% selectivity, which were more accurate than that of ANN with the same input size of raw data. In clinical result, our expert rule system, which uses neighboring channel informations, was capable of rejecting artifacts commonly found in EEG recordings.

Adolescent↗

PubMed2002

An expert system for the evaluation of EDSS in multiple sclerosis.

Multiple sclerosis is a disease of unknown aetiology. Despite several advances in therapy in recent years, some problems such as the prognostic criteria are imperfectly understood. Several experimental trials of therapy in multiple sclerosis are in course in order to discover a successful treatment. Most of these research studies use a clinical rating scale named Expanded Disability Status Scale (EDSS) as an evaluation tool for the effects of drugs. This scale is defined by a set of rules written in English which provide a numerical quantification of the neurological examination. Although EDSS has been widely used for almost 20 years, its application still depends on the interpretation of the neurologist who performs the neurological examination, and many applications of the scale performed by different neurologist on the same patient can give different results. This is a serious problem for international trials because they lack of a reliable measure of the effects of drugs. Here, we present an expert system for the automatic evaluation of EDSS in multiple sclerosis, which has been developed to overcome this problem. The expert system exploits an explicit representation of EDSS rules, it is able to explain its conclusions and it provides a revision tool to support the user if no satisfying solution can be reached. Using this expert system, clinical trials based on EDSS can benefit of a more reliable evaluation tool providing more valuable results.

Disability Evaluation↗

PubMed1990

An expert system for diagnosis of coronary artery stenosis based on 201Tl scintigrams using the Dempster-Shafer theory of evidence.

An expert system for the diagnosis of stenoses in the three main coronary arteries (left anterior descending, right coronary artery and circumflex) is described. First, the knowledge base domain--201Tl scintigrams--is explained and the method of preprocessing the original heart images is given. Next, the method of dealing with the uncertainties present both in the cardiologist-specified rules and the data using the Dempster-Shafer theory of evidence is explained. Finally, the constructed expert system and the results are discussed and several graphical examples are shown.

Coronary Disease↗

PubMed1992

CASSPERT--an expert system to guide choice and strategy in coronary angioplasty.

Coronary angioplasty is a technique widely used in the treatment of coronary artery disease. The success of coronary angioplasty depends on patient selection, the use of an appropriate technique, and to a large extent a carefully considered choice of angioplasty equipment. The authors have developed an expert system which can assist in this decision making process. CASSPERT was developed using the expert system shell 'Leonardo' running on a standard Personal Computer. The user interacts with CASSPERT to build up a detailed profile of clinical, investigational and angiographic features of the patient. This information, together with technical data stored within Leonardo's own object orientated database, is used to infer a suitable choice of equipment. To make the expert system useful in clinical practise, it was interfaced within a functional, readily accessible, data acquisition and storage environment which could be used within the day to day running of the department.

Angioplasty, Balloon, Coronary↗

PubMedDate not supplied

Obligations of the expert system builder: meeting the needs of the user.

Builders of expert systems have generally accepted the principle that computer software should not be subject to government regulation if health care practitioners can be expected to interpret and apply the systems intelligently. The purpose of this paper is to identify the information that builders must make available to permit health care practitioners to exercise their clinical judgment in interpreting and applying the output of computing systems.

Diagnosis, Computer-Assisted↗

PubMed1991

Extensions to the time-oriented database model to support temporal reasoning in medical expert systems.

Physicians faced with diagnostic and therapeutic decisions must reason about clinical features that change over time. Database-management systems (DBMS) can increase access to patient data, but most systems are limited in their ability to store and retrieve complex temporal information. The Time-Oriented Databank (TOD) model, the most widely used data model for medical database systems, associates a single time stamp with each observation. The proper analysis of most clinical data requires accounting for multiple concurrent clinical events that may alter the interpretation of the raw data. Most medical DBMSs cannot retrieve patient data indexed by multiple clinical events. We describe two logical extensions to TOD-based databases that solve a set of temporal reasoning problems we encountered in constructing medical expert systems. A key feature of both extensions is that stored data are partitioned into groupings, such as sequential clinical visits, clinical exacerbations, or other abstract events that have clinical decision-making relevance. The temporal network (TNET) is an object-oriented database that extends the temporal reasoning capabilities of ONCOCIN, a medical expert system that provides chemotherapy advice. TNET uses persistent objects to associate observations with intervals of time during which "an event of clinical interest" occurred. A second object-oriented system called the extended temporal network (ETNET), is both an extension and a simplification of TNET. Like TNET, ETNET uses persistent objects to represent relevant intervals; unlike the first system, however, ETNET contains reasoning methods (rules) that can be executed when an event "begins", and that are withdrawn when that event "concludes". TNET and ETNET capture temporal relationships among recorded information that are not represented in TOD-based databases. Although they do not solve all temporal reasoning problems found in medical decision making, these new structures enable patient database systems to encode complex temporal relationships, to store and retrieve patient data based on multiple clinical contexts and, in ETNET, to modify the reasoning methods available to an expert system based on the onset or conclusion of specific clinical events.

Diagnosis, Computer-Assisted↗

PubMed2005

[Research & development on computer expert system for forensic bones estimation].

OBJECTIVE: To build an expert system for forensic bones estimation. METHODS: By using the object oriented method, employing statistical data of forensic anthropology, combining the statistical data frame knowledge representation with productions and also using the fuzzy matching and DS evidence theory method. RESULTS: Software for forensic estimation of sex, age and height with opened knowledge base was designed. CONCLUSION: This system is reliable and effective, and it would be a good assistant of the forensic technician.

Age Determination by Skeleton↗