PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Expert Systems”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64Linked to original sources
PubMed1993

A knowledge based interpretation system for EMG abnormalities.

The conventional method of diagnosis in electromyography is complex and time consuming, not only due to the large number of parameters, to be considered for diagnosis, but also because of the usual procedure of evaluating the different parameters of EMG signal by visual scanning of the plotted signal. So there is a clear need to make use of computer aided decision support system. In the present work an attempt has been made in the direction of integration into one automated system, the qualitative knowledge of the physician, with possibly sophisticated signal analysis tools which must replace the visual scanning. A software program (in Turbo-C) on a PC-AT has been developed to evaluate the different parameters of MUAP's (motor unit action potential) in a EMG signal. Then an Expert system (in Turbo-Prolog) has been implemented for diagnostic purposes of different muscular abnormalities by making a knowledge base from the different parameters involved in the decision making procedure of clinical electromyography. A hybrid model of rule and frame based Expert system is implemented. An attempt has been made for making a complete system, i.e., for recording, analysis and decision making for diagnosis.

Diagnosis, Computer-Assisted↗
PubMed2005

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

Algorithms↗
PubMed2006

Preoperative diagnosis of 221 consecutive ovarian masses: scoring system and expert evaluation.

OBJECTIVE: The aim of our work was to assess the diagnostic accuracy of a scoring system versus subjective assessment of the risk of malignancy of pelvic masses achieved by gynecologist/sonologists in the preoperative triage of a busy gynecology department. METHODS: One hundred and eighty-two consecutive patients who underwent surgical removal of ovarian neoplasms were examined. In 39 patients pelvic masses were bilateral. The total number of neoplasms analyzed in this series was 221. Lesions were examined and scored according to the sonographic characteristics. Gynecologist/sonologists also recorded a subjective evaluation of the adnexal masses defining them as "probably benign", and "suspicious/probably malignant". Preoperative ultrasound risk assessment was compared to the final pathologic report and diagnostic accuracy was calculated. CA125 was obtained in all patients and its independent and combined accuracy was calculated. RESULTS: The sensitivity of the scoring system and subjective evaluation was 86% and 95% respectively, specificity was 79% and 91% with a positive predictive value of 41% and 53%. The frequency of positive diagnoses for CA125 was 44% due to the high prevalence of endometrosis in this series (48%). In premenopausal patients (75%) the specificity was 93% and 89% for scoring and subjective evaluation, respectively. The combined use of morphological scoring and CA125 achieved higher specificity and positive predictive values both for the whole series and in premenopausal patients. CONCLUSIONS: These results confirmed that the experience of gynecological surgeons with ultrasound skills, outperforms the morphological indexing assessment of ovarian masses. Nonetheless an easy sonographic descriptive scoring system is not significantly lower in accuracy than the expertise achieved by gynecologists with sonographic skills.

Adult↗
PubMedDate not supplied

Converting laserdisc video to digital video: a demonstration project using brain animations.

Interactive laserdiscs are of limited value in large group learning situations due to the expense of establishing multiple workstations. The authors implemented an alternative to laserdisc video by using indexed digital video combined with an expert system. High-quality video was captured from a laserdisc player and combined with waveform audio into an audio-video-interleave (AVI) file format in the Microsoft Video-for-Windows environment (Microsoft Corp., Seattle, WA). With the use of an expert system, a knowledge-based computer program provided random access to these indexed AVI files. The program can be played on any multimedia computer without the need for laserdiscs. This system offers a high level of interactive video without the overhead and cost of a laserdisc player.

Audiovisual Aids↗
PubMed1990

Chaotic behavior in excitable systems.

This paper has dealt with biophysically accurate, or plausible, excitation systems. These are obtained from experiments, and so are complicated, often of high order, and are continually being updated by new experimental results. This is especially true for the excitation equations that represent cardiac tissue. Biophysically relevant problems require quantitatively accurate answers: What happens at what values of what parameter? Thus, numerical methods and results are important, and there is a strong tendency for both the model and the method of analysis to be given as computer algorithms; a current model for cardiac membrane dynamics is a computer package, and the use of path tracking procedures such as AUTO or PATH is becoming common. Perhaps the best way to proceed in the investigation of complicated and exotic dynamics in models of cardiac tissue would be to combine model formulation from voltage clamp data (the derivation of the excitation equations) with bifurcation, and even perhaps singularity theory analysis of dynamical systems, into an expert system.

Action Potentials↗
PubMedDate not supplied

Inappropriateness of cataract extraction: an analysis in two Israeli hospital settings.

OBJECTIVE: To assess and compare the appropriateness of cataract extraction in two Israeli regional hospitals. SETTINGS: Two Israeli hospitals located in different geographic areas. DESIGN: A randomized sample of 150 patients was drawn from a list of all patients who underwent cataract surgery at the two study hospitals during 1995. Detailed extraction of hospital medical records was performed. The appropriateness of cataract surgery was assessed using the Medical Review System, an interactive expert system that assesses the appropriateness of selected medical and surgical procedures. RESULTS: The rates of cataract surgery in the two hospitals were 0.54 and 0.59 operations per 1,000 population, respectively, and the age-adjusted rates per 1,000 population were 5.7 and 6.2, respectively. The percentage of patients with only light perception or hand-motion perception in the operated eye before the operation was 62.2%, with no difference in the two hospitals. There was not a significant difference in the distribution of visual acuity before the operation; however, there was a significant difference in the distribution of visual acuity after the surgery. Rates of inappropriate surgeries in the two hospitals were found to be similar to the inappropriate rate in the United States (1.3%). The preoperative visual acuity of patients undergoing cataract surgery in Israel was inferior to the visual acuity of patients undergoing cataract surgery in the United States. CONCLUSION: To increase quality and cost-effectiveness in the Israeli medical system, future studies of this type are warranted in connection with surgical procedures.

Cataract Extraction↗
PubMed2002

Automated fault-management in a simulated spaceflight micro-world.

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

Adult↗
PubMed2003

Diagnoses, syndromes, and diseases: a knowledge representation problem.

Despite their widespread use, the terms "syndrome", "disease" and "diagnosis" are sometimes utilized improperly and ambiguously, compounding the complexities of medical knowledge representation. The definitions and illustrative examples provided here will be useful for developers of diagnostic expert systems. Description of the Problem Representing medical knowledge is a highly complex endeavor. The improper use of the terms "syndrome", "disease" and their relations to "diagnosis" is one of the difficulties with which medical informaticians must deal, especially when developing expert systems to support diagnoses. Although ubiquitous in medical and lay discourse, the term "disease" has no unambiguous, generally accepted definition. How-ever, most of those using this term allow themselves the comfortable delusion that everyone knows what it means. Only sparse and fragmented literature could be found regarding this issue.

Diagnosis↗
PubMed1996

Artificial intelligence in pediatrics: important clinical signs in newborn syndromes.

New methods are warranted in the field of syndromology. This study is an exploration into whether an artificial intelligence method (ID3) could provide a new angle for approaching syndromes. Diagnosing syndromes in the newborn is difficult. The accepted approach is to look for individual clinical signs that add up to a syndrome diagnosis. Of all possible clinical signs, one would want to extract the signs with the strongest predictive power. I used the ID3 algorithm to extract predictive clinical signs from a catalogue of syndromes (Birth Defects Encyclopedia Online; BDEO). Using information from BDEO, files of randomly generated "patients" were created. The signs consistently high in the identification tree were long philtrum, short palpebral fissures, low-set ears, and hepatosplenomegaly. The program used featured a crude "expert system" based on the ID3 algorithm. When using one-half of the data set as a training set and the other half as a testbed, a correct classification rate of 92.1-98.1% was attained. When the ID3 expert system was tested against cases from a clinical database (Pictures of Standard Syndromes and Undiagnosed Malformations), the correct classification rate was less than 20%. This may not necessarily reflect faults with the ID3 approach, but possibly biases in the clinical database. In syndromology no "criterion standards" exist that can confirm a diagnosis. The statistical method of cluster analysis does not require prior knowledge of diagnoses and will make a tree of syndromes based upon clinical signs. A cluster analysis was performed as a validity check to provide a tree for comparison with the ID3 tree. There was a reasonable degree of agreement between the two. Applying artificial intelligence methods to this field highlights problems with basic assumptions and philosophical aspects of syndrome diagnosis.

Algorithms↗
PubMed1989

The role of smart medical systems in the Space Station.

NASA is developing a Health Maintenance Facility to provide medical equipment and supplies requisite for the Space Station to be launched in the late 1990s. An essential component of this medical facility is a computerized Medical Decision Support System which will expedite medical officers' efforts to maintain the crew's health. The computerized system includes four major functions: 1. A data collection and storage system with a self-contained medical expert scheme for performing treatment protocols. The expert system has 'data driven' and 'time driven' capabilities to facilitate automatic decision-making functions. 2. An integrated medical record and medical 'reference' information management component. 3. An inventory management system for medical supplies and pharmaceuticals. 4. Video, audio, and data communications between the medical officer in the Space Station and ground-based medical personnel. This paper discusses the design of such computerized data collection, communications and expert medical systems as will be developed for use in a Space Station Health Maintenance Facility.

Aerospace Medicine↗
PubMed2004

Construction, training and clinical validation of an interpretation system for genotypic HIV-1 drug resistance based on fuzzy rules revised by virological outcomes.

OBJECTIVES: To evaluate whether fuzzy operators can be usefully applied to the interpretation of genotypic HIV-1 drug resistance by experts, and to improve the prediction of salvage therapy outcome by adapting interpretation rules of genotypic resistance on the basis of their association with virological response data. METHODS: We used a clinical dataset of 231 patients failing highly active antiretroviral therapy (HAART) and starting salvage therapy with baseline resistance genotyping and virological outcomes after 3 and 6 months. A set of rules predicting genotypic resistance was initially derived from an expert (ADL). Rules were implemented using a fuzzy logic approach and the virological outcomes dataset used for the training phase. The resulting algorithm was validated using a separate set of 184 selected patients by correlating the resulting predicted activity with observed virological response at 3 months. For comparison, the expert systems from the drug resistance group of the Agence Nationale de Recherches sur le SIDA (ANRS-AC11) and the algorithm from the Stanford's HIV drug resistance database (Stanford HIVdb) were evaluated on the same set. RESULTS: The starting algorithm had a correlation with virological outcomes of R2=0.06 (P=0.0001). After the training phase the correlation with virological outcomes increased to R2=0.19 (P<0.000001). In the validation set of patients, the activity of the salvage regimen predicted by the fuzzy algorithm was the only variable independently predictive of the 3-month viral load change even after adjusting by the activity predicted by the two expert systems and baseline viral load (for each 10% salvage regimen's activity increase, mean HIV RNA change from baseline: -0.27 log10 copies/ml; 95% CI -0.39, -0.15). CONCLUSION: Using fuzzy operators in a virological outcomes training database to implement a rules-based algorithm for genotypic resistance interpretation, significant improvements of outcomes prediction were obtained. The resulting algorithm showed an independent predictive capability of virological outcomes over that of two rules-based interpretation algorithms made by experts. Although the system was trained and validated on a limited number of cases, the approach deserves further evaluation.

Adolescent↗
PubMed1990

Computer-aided diagnosis and treatment of malaria: the IMEX system.

IMEX is a prototype Integrated Malaria EXpert system whose practical objectives are to act as a tool to assist medical personnel in the diagnosis and treatment of malaria, to improve management of malaria patients and to formalize and document knowledge on malaria. This paper describes some of its important features, both from the user's point of view, as well as the technical aspects. The design of IMEX has taken into account practical considerations like cost, ease of usage and integration with its working environment. An evaluation of IMEX and some enhancements which can be made to the prototype are also discussed.

Diagnosis, Computer-Assisted↗
PubMed1989

Description of a blockcourse in medical informatics.

This paper describes a blockcourse in medical informatics. The course is presented to fourth, fifth and sixth year medical students and lasts one week. During the course all aspects of medical informatics are considered. Programming, databases, information systems, signal analysis, pattern recognition, expert systems, etc. are explained. Lectures alternate with hands-on experience. The subjects discussed in the lectures are rehearsed during the practical sessions, so that gaps in the student's knowledge are immediately detected. The blockcourse has been positively rated by the students.

Computer-Assisted Instruction↗
PubMed1988

A gentle introduction to knowledge-based systems in medicine.

In summary, AI expert systems, through the example of medical problem solving, have been examined, considering goals, problems addressed, and problems resolved (or not resolved). How these systems attempt to replicate the knowledge and strategies of human experts has been shown, as well as how they determine these factors (in the form of the protocol). Through the example of diagnosis, some of the types of knowledge and approaches such systems must encode have been illustrated. Concrete examples of approaches to encoding were presented using MYCIN and PIP. These systems demonstrate more clearly the complexity of the problem domains under consideration, how that complexity can be dealt with, and the limitations and potential of AI. It is apparent that such systems have unique contributions to make, not only in terms of straightforward usefulness but also in terms of inspectability, which may be extended to a capacity for "explaining." On a more basic level, they are generating a reexamination of what is considered "intelligent" behavior--which may itself lead to future concepts, systems, and tools. Moreover, the fundamental goal of generality in the design of AI systems makes such things as, for example, the hypothetico-deductive model of behavior transferrable across domains, conferring a similar ability for revitalization and reexamination in each one.

Clinical Protocols↗
PubMed2005

Development of a reliable automatic speed control system for rotary blood pumps.

BACKGROUND: Axial blood pumps have been very successfully introduced into the arena of prolonged clinical support. However, they do not offer inherent load-responsive mechanisms for adjusting pumping performance to venous return and changes in physiologic requirements of the patient. To provide for these adjustments we developed an algorithm for demand-responsive pump control based on a reliable suction detection system. METHODS: A PC-based system that analyzes pump performance based on available flow, heart rate and short-term performance history was developed. The physician defines levels of "desired flow" at rest and during exercise, depending on heart rate. In case this desired flow cannot be maintained due to limited venous return, the maximal available flow level is determined from an analysis of the actual pump data (flow, speed and power consumption). An expert system continuously checks the flow signal for any indication of suction. Periodic speed variations then adapt pump performance to the patient's condition. RESULTS: First, stability and functionality were proven under various settings in vitro. The algorithms were then tested in 15 patients in intensive care, in the standard ward, and during bicycle exercise. The system reacted properly to demand changes, at exercise level, in response to coughing and at various Valsalva maneuvers. Suction could also be successfully prevented during severe arrhythmia and in patients with critical cardiac geometry. Exercise tests showed decreases in pulmonary arterial pressure (-22 +/- 9.9%) and pulmonary capillary wedge pressure (-42 +/- 18.54%), and an increase in pump flow (19 +/- 9.5%) and workload (8 +/- 6.1%), all when compared with constant-speed pumping. CONCLUSIONS: A closed-loop control system equipped with an expert system for reliable suction detection was developed that improves response to change in venous return for rotary pump recipients. The system was robust, stable and safe under a wide range of everyday living conditions.

Algorithms↗
PubMed2003

Contact allergy: the role of skin chemistry and metabolism.

Chemical reactivity plays the driving role in the biological processes that result in the induction of allergic contact dermatitis. This paper presents an overview of the chemical basis of allergic contact dermatitis, including the physicochemical parameters governing skin penetration, chemical reaction mechanisms associated with haptenation of skin proteins, (quantitative) structure-activity relationships (Q)SARs for contact allergens and prohaptens/skin metabolism of contact allergens. Despite the complexities and poor understanding of some of the metabolic processes leading to skin sensitization, it is possible to describe some of the relationships between chemical structures and the ability to form covalent conjugates with proteins. This knowledge, which relates chemical structure to a specific endpoint, can be programmed into an expert system. The Deductive Estimation of Risk from Existing Knowledge (DEREK) is one such expert system which is described in further detail.

Allergens↗
PubMed1993

Computerized interactive morphometry and the diagnosis of lymphoid-rich effusions.

An experimental computerized interactive morphometry system for the classification of lymphoid-rich effusions is presented. The relatively inexpensive microcomputer-based system was assembled in our laboratory with commercially available hardware and software. One hundred twenty-two effusions (86 benign lymphocytoses, 26 lymphomas, and 10 chronic lymphocytic leukemias) were studied. Lymphoid cells were selected randomly by the system from real-time images of Papanicolaou-fixed and stained cytospin smears of pleural, peritoneal, and pericardial effusions. Parameters of nuclear shape, area, and optical density were measured automatically. Multiparameter statistical procedures of discriminant classificatory analysis analyzed the distribution of lymphoid nuclear profile integrated optical density to yield three groups of effusions, each with a predictive value of diagnosis of 100%. Neither these statistical procedures nor a simple rule-based expert system accurately classified chronic lymphocytic leukemia effusions based on the distribution of lymphoid nuclear profile area. When chronic lymphocytic leukemia effusions were excluded, however, the predictive values of a diagnosis of lymphoma by statistical analysis and by rule-based expert system were 92.3% and 88.9%, respectively, whereas the predictive values of a diagnosis of benign lymphocytosis were 97.7% and 91.3%, respectively. Potential applications and limitations of this technology for the diagnosis of lymphoid-rich effusions are discussed.

Cell Nucleus↗