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PubMed1996

Temporal logics and real time expert systems.

This paper introduces temporal logics. Due to the eternal compromise between expressive adequacy and reasoning efficiency that must decided upon in any application, full (first order logic or modal logic based) temporal logics are frequently not suitable. This is especially true in real time expert systems, where a fixed (and usually small) response time must be guaranteed. One such expert system, Fagan's VM, is reviewed, and a delineation is given of how to formally describe and reason with time in medical protocols. It is shown that Petri net theory is a useful tool to check the correctness of formalised protocols.

Expert Systems↗

PubMed1994

Demonstration of a neural network expert system for recognition of glaucomatous visual field changes.

Expert systems (ESs) are computer programs designed to make decisions in a manner similar to the way human experts make them. There are many forms of ESs, ranging from those that are given specific If-Then rules to those that are capable of deriving their own rules. Some ESs use neural network simulations to analyze patterns of data. In this project, a commercially available neural network shell program was used to demonstrate the development of an ES capable of analyzing the visual field loss patterns produced by glaucoma. Potential applications of ESs for the diagnosis of glaucoma are discussed.

Decision Making, Computer-Assisted↗

PubMed1987

Medical diagnosis: are expert systems needed?

An evaluation of the pitfalls of computer-aided diagnosis during the last ten years seems to show that increased emphasis on real clinical problems as well as increased use of medical knowledge are required. Since such an approach could fit into the 'expert system' framework, one should expect new developments in that research field to occur soon. However, expert systems can also be designed along the same concepts as previous models of diagnostic reasoning presumably with the same shortcomings.

Diagnosis, Computer-Assisted↗

PubMed1995

Development of a connectionist expert system to identify foot problems based on under-foot pressure patterns.

The first phase of developing a connectionist expert system is described in this study. Dynamic pressure patterns below the foot obtained by the emed f system of 18 subjects were classified into one of the three categories: normals, pes cavus and hallux valgus. As opposed to the traditional approach for the analysis of the pressure patterns by quantifying isolated segments, a neural network based expert system was trained to perform objective classification of the patterns while keeping their integrity. The results of the backpropagation paradigm were unexpectedly good considering the limiting factors which hindered the performance of the neural networks. The successes indicate the potential of artificial intelligence in automated analysis of foot pathologies based on theemed f system. RELEVANCE:--This paper describes the first steps towards a novel automated screening system, which classifies the patient with foot abnormalities into the pathological category he or she belongs to, based on the pressure pattern below the foot. The decision making is objective, and shows a practical example of the use of artificial intelligence.

Journal Article↗

PubMedDate not supplied

TREACT. An expert system consultation program to aid in the diagnosis of transfusion reactions.

We have developed a rule-based, expert system consultation program, TREACT, to aid in the diagnosis of transfusion reactions. Given clinical signs, symptoms, and laboratory results, the program generates diagnoses, alerts the user when a medical director should be called, suggests follow-up actions, and makes recommendations for future transfusion. Diagnoses made by TREACT, including 121 reactions, were compared with those of the medical directors over a 6-month period. The overall diagnostic concordance between the medical directors and the program was 0.777. When this was corrected for chance association (kappa statistic), the concordance was 0.703 (p less than 0.0001), which can be interpreted on a qualitative scale as substantial agreement. The program has also been used successfully as a tool for training new technologists. Other advantages and possibilities that expert systems offer to transfusion medicine are discussed.

Diagnosis, Computer-Assisted↗

PubMed1995

Second opinion: a computer expert system designed to aid in the determination of spectacle lens prescriptions.

BACKGROUND: Expert systems (ESs) are computer programs that simulate the decision-making ability of human experts. In this project, an ES was developed that used optometric data and decision rules to determine spectacle lens prescription powers. METHODS: Decision rules derived from clinical experience and standard references were provided to a commercially available shell program to create an ES called Second Opinion. The ES determined spherical, cylindrical, and add powers designed to provide maximum acuity consistent with a high probability of patient acceptance. CONCLUSIONS: Second Opinion demonstrates how a computer program can be used to analyze optometric data and offer suggestions regarding lens prescriptions.

Adult↗

PubMed1994

HYCONES II: a tool to build hybrid connectionist expert systems.

This paper describes HYCONES II--a tool to enable the construction of hybrid connectionist expert systems to solve classification problems. HYCONES II offers to the knowledge engineer a hybrid knowledge base that integrates frames with three different neural network models: the combinatorial neural model--CNM, the Fuzzy ARTMAP and the Semantic ART--SMART models. The latter is a new model, introduced by this paper, based on a combination of the two previous models. The validation section compares the performance of these three neural models to solve diagnostic problems in two medical domains. This paper also presents HYCONES II knowledge representation features, built in the symbolic component of its hybrid knowledge-base, to deal and represent fuzzy medical variables. Finally, the present status and future developments of the project are presented.

Algorithms↗

PubMed1986

Expert systems for medical consultation.

After reviewing some of the elements that permit a clearer understanding of what characterizes the "expert systems" approach, representation of medical concepts, symbolic manipulation rather than numeric calculation, causal reasoning, etc., this paper will try to deal with some of the most noteworthy developments in medical decision aid, teaching, research, before discussing some problems raised by the evaluation of expert systems in medicine.

Artificial Intelligence↗

PubMed1986

Medical expert systems--knowledge tools for physicians.

Recent advances in the field of artificial intelligence have led to the emergence of expert systems, computational tools designed to capture and make available the knowledge of experts in a field. Although much of the underlying technology available today is derived from basic research on biomedical advice systems during the 1970s, medical application packages are thus far generally unavailable from the young artificial intelligence industry. Medical expert systems will begin to appear, however, as researchers in medical artificial intelligence continue to make progress in key areas such as knowledge acquisition, model-based reasoning and system integration for clinical environments. It is accordingly important for physicians to understand the current state of such research and the theoretic and logistic barriers that remain before useful systems can be made available. One experimental system, ONCOCIN, provides a glimpse of the kinds of knowledge-based tools that will someday be available to physicians.

Drug Therapy, Computer-Assisted↗

PubMed1994

Interfacing a stand-alone diagnostic expert system with a hospital information system.

Few diagnostic decision-support systems are in routine clinical use, mainly because these systems typically require time-consuming manual data entry. This research investigated the feasibility of reducing manual data entry by integrating a stand-alone diagnostic expert system with an existing comprehensive hospital information system (HIS). A knowledge-based intervocabulary mapping technique was developed to map disparate vocabularies. The results of a retrospective study indicate that transferring clinical data from the HIS to the diagnostic expert system at the beginning of workup significantly reduces the manual data entry required for generating the correct diagnoses for patients.

Diagnosis, Computer-Assisted↗

PubMed1994

[An expert system for the planning of whole-body irradiation treatments].

Total body irradiation (TBI) combined with intensive chemotherapy and bone marrow transplantation is used with increasing success for the treatment of hematologic malignancies with severe prognosis. An expert system, developed on the basis of the experience acquired during the last years in our department, has been designed to optimize the different treatment steps. The choice of an expert system is based on its capabilities in reconstructing a rule-based reasoning through the combination of theoretical and empirical knowledge. Particularly, a subsystem dealing with the steps to be taken to optimize treatment in TBI has been designed using medical and physical data. Our system can determine radiation treatment variables together with a sequence of quality control procedures. Moreover, indications are given about short, medium and long term damage probabilities and toxicity estimates, both derived from literature data and our personal series of cases. Treatment quality can be assessed and the different techniques compared using these data. This project is aimed at providing physicians and physicists with useful clinical suggestions for TBI setting for bone marrow transplantation.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed1993

Real-time expert systems interfaces, cognitive processes, and task performance: an empirical assessment.

In this experiment we investigated the effect of different real-time expert system interfaces on operators' cognitive processes and performance. The results supported the principle that a real-time expert system's interface should focus operators' attention on where it is required most. However following this principle resulted in unanticipated consequences. In particular, it led to inferior performance for less critical, yet important cases requiring operators' attention. For such cases operators performed better with an interface that let them select where they wanted to focus their attention. Having a rule generation capability improved performance with all interfaces but did so less than hypothesized. In all cases performance with different interfaces and a rule generation capability was explained by the effect of the interfaces on cognitive process measures.

Aircraft↗

PubMed1995

NEUREX: a tutorial expert system for the diagnosis of neurogenic diseases of the lower limbs.

Specialist tutors have to transfer two types of knowledge to doctors who are specialising in a particular clinic: public declarative knowledge, including facts, notions, principles in that particular field; and their own private procedural knowledge acquired in years of direct experience. Embodying this knowledge into an expert system means that this information can be shared more rapidly, and tutoring is easier. This paper presents a tutorial expert system for neurological clinics which can emulate the diagnostic process of an expert neurologist for neurogenic diseases of the lower limbs, assist users in planning the optimal sequence of NG and EMG tests, interpret the results of these tests, and help users to achieve the most suitable diagnosis.

Diagnosis, Computer-Assisted↗

PubMed1997

Application of fuzzy reasoning in an expert system for ultrasonography.

OBJECTIVES: To apply fuzzy reasoning in a computer-assisted diagnostic system for ultrasonography and to evaluate its clinical utility as a diagnostic aid for the unskilled clinician. METHODS: A computer-assisted diagnostic system for ultrasonography was constructed to differentiate metastatic from inflammatory lymph nodes. The pattern of a skilled clinician's considerations was simulated with the fuzzy expert system. Three fuzzy production rules were set up according to the diagnostic criteria for lymphadenopathy. Each rule was transformed into a membership function. The max-min composition method was used for inference and the centroid method for defuzzification. The system was tested with 20 clinicians who were one to three years after graduation and inexperienced in ultrasonography. Accuracy, sensitivity and specificity were evaluated. RESULTS: The average increase in accuracy was 8.5%, and the sensitivity and specificity 10.7% and 6.4% respectively. These scores were significant for accuracy (P = 0.005), sensitivity (P = 0.02) and specificity (P = 0.036). CONCLUSIONS: Application of fuzzy reasoning in an expert system for ultrasonography improves the diagnostic performance of inexperienced clinicians.

Clinical Competence↗

PubMed1998

An expert system for assigning patients into clinical trials based on Bayesian networks.

Assigning patients into clinical trials is a knowledge and data intensive task. Eligibility determination for entry into a clinical trial is based upon specific inclusion and exclusion criteria. This paper investigates the use of an excerpt system to assist the physician through this task. This expert system uses Bayesian networks, a probabilistic method that can take advantage of pre-existing statistical knowledge. The paper also describes the feasibility of such a system by presenting the implementation of three clinical protocols. The experimental results reveal that the approach is feasible. The system gives correct eligibility scores when all evidence is available but also predicts eligibility when there is missing evidence. The system directs the physician to the protocols the patient is most eligible for, according to the current evidence. The system has the ability of learning its prior and conditional probabilities (expert knowledge) from training examples.

Algorithms↗

PubMed1999

The evaluation of an expert system for the analysis of umbilical cord blood.

An assessment of neonatal outcome may be obtained from analysis of blood in the umbilical cord of an infant immediately after delivery. This can provide information on the health of the new-born infant, guide requirements for neonatal care, but there are problems with the technique. Samples frequently contain errors in one or more of the important parameters, preventing accurate interpretation and many clinical staff lack the expert knowledge required to interpret error-free results. The development and implementation of an expert system to overcome these difficulties has previously been described. This expert system validates the raw data, provides an interpretation of the results for clinicians and archives all the results, including the quality control and calibration data, for permanent storage. Issues regarding the clinical evaluation of this system are now detailed further, along with some clinical results illustrating the potential of such a system.

Acid-Base Equilibrium↗

PubMed1992

Diagnostic function of the microhuman prototype of the expert system--MUNIN.

This paper describes the diagnostic function of a prototype expert system for electromyography (EMG). The prototype was restricted to a limited "Microhuman" anatomy with only 6 muscles and 8 nerves, and a corresponding limitation on the number of local nerve lesions. It attempted to give a detailed description of the most important groups of generalized nerve and muscle disorders, and the commonly used parameters from needle EMG and nerve conduction studies were included. The system can be used both for "diagnostic" and for "causal" reasoning. In diagnostic reasoning, the system's probabilistic inference engine is used to reason from test results through 14 different aspects of neuromuscular pathophysiology to disorders. In causal reasoning, the system reasons in the opposite direction from disorders through pathophysiology to expected test results. The diagnostic function of the system was illustrated by 3 cases: a normal subject, a patient with a bilateral carpal tunnel syndrome and a patient with both a diabetic polyneuropathy and a bilateral carpal tunnel syndrome.

Carpal Tunnel Syndrome↗

PubMed1996

[The prototype of an expert system for the diagnosis of pseudotumorous lesions and tumors of the jaws: ADAPT-M. Archiviazione e Diagnosi Automatica di Pseudotumori e Tumori delle ossa Mascellari].

Many different tumors and pseudotumors may affect the jaw bones. The number and the rarity of most of these lesions, however, make both classification and differential diagnosis quite difficult. Computer software for statistical calculations and logical-deductive reasoning on vast amounts of data can improve diagnostic skills. These applications are defined as computer-assisted decision-making, medical decision support, or expert systems. This study was aimed at developing a prototype probabilistic expert system, based upon knowledge from an "ad hoc"computerized data base, as an aid in the radiologic diagnosis of jaw tumors and pseudotumors. This program has been called ADAPT-M. The study considered 92 patients with benign space-occupying and fully documented lesions of the jaw bones. For each case, a list of parameters concerning different radiologic exams was considered. From all these pieces of information a data base was built, to calculate both the prevalence of each type of lesion and the frequency of many variables in the single conditions. For each kind of lesion 44 variables were considered. ADAPT-M used a formula based on Bayes' theorem to calculate the "a posteriori" probability of a diagnosis in the presence of a symptom. Overall diagnostic probability rate was high when the highest score hypothesis was matched with pathologic findings (80%) and even higher (96.1%) when the two most probable diagnoses were considered together. As expected, ADAPT-M had higher sensitivity when used with lesions with typical semiology. This results in an unquestionable limitation, especially in the patients in whom a predictive diagnosis would be most desirable. The creation of a larger data base of known cases and software development may help increase the diagnostic accuracy of the ADAPT-M system.

Databases, Factual↗