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PubMed2004

KASER: Knowledge Amplification by Structured Expert Randomization.

In this paper and attached video, we present a third-generation expert system named Knowledge Amplification by Structured Expert Randomization (KASER) for which a patent has been filed by the U.S. Navy's SPAWAR Systems Center, San Diego, CA (SSC SD). KASER is a creative expert system. It is capable of deductive, inductive, and mixed derivations. Its qualitative creativity is realized by using a tree-search mechanism. The system achieves creative reasoning by using a declarative representation of knowledge consisting of object trees and inheritance. KASER computes with words and phrases. It possesses a capability for metaphor-based explanations. This capability is useful in explaining its creative suggestions and serves to augment the capabilities provided by the explanation subsystems of conventional expert systems. KASER also exhibits an accelerated capability to learn. However, this capability depends on the particulars of the selected application domain. For example, application domains such as the game of chess exhibit a high degree of geometric symmetry. Conversely, application domains such as the game of craps played with two dice exhibit no predictable pattern, unless the dice are loaded. More generally, we say that domains whose informative content can be compressed to a significant degree without loss (or with relatively little loss) are symmetric. Incompressible domains are said to be asymmetric or random. The measure of symmetry plus the measure of randomness must always sum to unity.

Algorithms↗

PubMed2001

[Progress in knowledge-based X-ray fluorescence spectrometry].

The review focuses on the expert systems and knowledge engineering in X-ray fluorescence spectrometry. It includes mainly a knowledge-controlled strategy combining the scan-based method with the fixed channel measurements, a XRF interpretation system of spectra with fuzzy logic and pattern recognition, and an expert system for qualitative interpretation of XRF spectra using a certainty factor. In the review, a series of the studies of exploring the knowledge engineering system in XRF are also included, which consists of four parts, i.e. spectra identification, pattern recognition with decision-making, quantitative determination combined with the theoretical alpha coefficients and neural networks, and XRF analysis without standards.

Algorithms↗

PubMed1994

Image cytometry: current applications and future trends.

Image cytometry has numerous clinical and research applications and is particularly useful in anatomic pathology for the study of malignant lesions. Modern image systems encompass morphometry, densitometry, neural networks, and expert systems. Rapid advances in technology and the development of user-friendly systems have provided pathologists with an alternative to flow cytometry, particularly useful in the evaluation of small or hypocellular specimens. The most common current application of image cytometry is for DNA analysis, followed by quantitation of immunohistochemical staining. Newer uses under active investigation include development of expert systems that may act as diagnostic consultants in the future. Beyond DNA analysis, image cytometry holds great promise for improved tumor classification, for screening and surveillance in high-risk populations, and as a tool to improve diagnostic ability. This article discusses types of image analysis systems, specimen preparation, data acquisition, current applications in specific organ sites, and possible future applications.

Cell Division↗

PubMed2003

Web and mobile secure access to a Web based medical system.

This paper describes the implementation of the Web Based Pneumonia Chemotherapeutics (WPCh) a Web-based expert system for chemotherapeutic assistantship for nosocomial and community-acquired pneumonia based on different types of data. WPCh can be accessed through World Wide Web or a mobile phone using the relevant script languages. The core of the paper focuses on the usage of security of data and the procedures used to accomplish this task. After the log in of the physician, he can take advantage of the various modules of the expert system in order to view chemotherapeutics and save the data that he prefers. The whole procedure can be followed through the interfaces of wap technology.

Community-Acquired Infections↗

PubMed2006

An XML-based framework for personalized health management.

This paper proposes a framework for personalized health management. In this framework, XML technology is used for representing and managing the health information and knowledge. Major components of the framework are Health Management Prescription (HMP) Expert System and Health Information Repository. The HMP Expert System generates a HMP efficiently by using XML-based templates. Health Information Repository provides integrated health information and knowledge for personalized health management by using XML and relational database together.

Humans↗

PubMed1994

The evaluation of expert diagnostic systems. How to assess outcomes and quality parameters?

Improvement of the quality in health care and the assessment of health outcomes of medical technologies have attracted an increasing attention in the implementation phases. In this paper 10 recent evaluation studies are reviewed to investigate to what extent they reflect the structure, process, and outcome of the conceptual framework. It is found that all the evaluation studies focus on structure measures. But if computer programs to support medical decision making are to be considered in the planning process of the health care system, the evaluation studies must strive to evaluate process and outcomes measures as well. A proposal for a framework for this kind of exploratory and evaluative research is outlined.

Diagnosis, Computer-Assisted↗

PubMed1992

Treatment time for Amersham caesium-137 manual afterloading system.

Currently, the Amersham caesium-137 afterloading system is widely used for gynecological treatment of tumors in uterine cervix. This paper introduces an expert system to determine the time of exposure of an Amersham afterloading system based on different combinations of applicator sources. The efficiency of the expert system achieves 93% of the clinical decisions taken by physicians. It is evaluated by both the experimental results and the actual clinical decisions.

Brachytherapy↗

PubMed1996

Body height changes with hyperextension.

OBJECTIVE: To automatize the lumbar physical examination with an acceptable rate of error. DESIGN: An external skin marker method for automatizing the physical examination was developed and its ability to discriminate between normal and abnormal subjects tested in a blind clinical trial. BACKGROUND: The low reproducibility of clinical findings, even among experienced doctors, has been well documented. This is of particular concern and may explain why there is such a wide variation in surgical rates across the USA (tenfold for disc herniation). Inconsistencies among physicians in the evaluation of benign low back conditions make standardization desirable. METHODS: A computerized physical examination was used to evaluate patients with low back pain and compare their results with a normative database obtained from a selection of healthy subjects. A high-resolution motion analysis system tracked the movement of skin markers placed on the midline and pelvis. Surface EMG electrodes placed above L(5) collected data from multifidus. From the kinematics of skin markers during flexion--extension with lifts up to 32 kg, and lateral bending with lifts up to 10 kg, the following parameters were estimated: lumbosacral angle and elongation, contribution of each lumbar segment to the lordosis reduction, relative pelvic/spine motion, and trunk velocity. First the average normal value for each estimated parameter was determined using 40 normal subjects. For each subject the difference between his parameter and the normal was processed by an expert system generating a normality index varying from zero (perfect abnormal) to one (perfect normal). To develop the expert system's rules, a preliminary group of 20 very abnormal subjects was used, such that the normality index separated them from the normals. For validation, a set of 29 back-sprain patients and another set of 42 discogram-positive patients were selected. Each subject was tested and his computerized normality index calculated without any clinician's input, then compared with the clinician's evaluation, which was taken to be the gold standard. The receiver operating characteristic technique was used to quantify the discrepancies. RESULTS: The expert system could detect clinically abnormal subjects with accuracy (sensitivity 83-91% and specificity > 90%) whele providing quantitative information on workers' functional capacities. CONCLUSIONS: Once a reference normative database is agreed upon, each patient can be compared with that reference according to the same rules, with the resulting machine classification being independent of the clinician. This eliminates the inter- and intra-clinician variability in patient follow-up. Because of the severity of the selection criteria, this study is based upon a relatively restricted number of subjects, as well as a limited normative database of 40 subjects. RELEVANCE: It is possible to automate the lumbar physical examination with an acceptable error rate. This technique permits the objective consistent assessment of lumbar function, and thus allows the comparison of different treatment regimes for lumbar dysfunction.

Journal Article↗

PubMed1996

Can the computerized physical examination differentiate normal subjects from abnormal subjects with benign mechanical low back pain?

Inconsistencies among physicians in the evaluation of benign low back conditions make standardization desirable. A computerized physical examination device was used to evaluate low back pain patients and compare their results with a normative database obtained from a selection of healthy subjects. A high-resolution motion analysis system tracked the movement of skin markers placed on the midline and pelvis. Surface electromyography electrodes placed above L(5) collected data from multifidus. From the kinematics of skin markers during flexion extension with lifts up to 32 kg, and lateral bending with lifts up to 4.6 kg, the following parameters were estimated: lumbosacral angle and elongation, contribution of each lumbar segment to the lordosis reduction, relative pelvic/spine motion and trunk velocity. First, the average normal value for each estimated parameter was determined using 40 normal subjects. For each subject, the difference between his parameter and the normal was processed by an expert system generating a normality index varying from zero (perfect abnormal) to one (perfect normal). To develop the expert system's rules, a preliminary group of 20 very abnormal subjects were used, such that the normality index separated them from the normals. For validation, a set of 29 WCB sprain patients and another set of 42 discogram positive were selected. Each subject was tested and his computerized normality index calculated without any clinicians' input. The computerized normality index was compared with the clinicians' evaluation which was taken to be the gold standard. The Receiver Operating Characteristic technique was used to quantify the discrepancies. Results show that the expert system can detect clinically abnormal subjects with accuracy (sensitivity 83-91% and specificity >/=90%) while providing quantitative information on workers' functional capacities.

Journal Article↗

PubMed1996

Artificial neural network to assist psychiatric diagnosis.

BACKGROUND: Artificial Neural Network (ANN), as a potential powerful classifier, was explored to assist psychiatric diagnosis of the Composite International Diagnostic Interview (CIDI). METHOD: Both Back-Propagation (BP) and Kohonen networks were developed to fit psychiatric diagnosis and programmed (using 60 cases) to classify neurosis, schizophrenia and normal people. The programmed networks were cross-tested using another 222 cases. All subjects were randomly selected from two mental hospitals in Beijing. RESULTS: Compared to ICD-10 diagnosis by psychiatrists, the overall kappa of BP network was 0.94 and that of Kohonen was 0.88 (both P < 0.01). In classifying patients who were difficult to diagnose, the kappa of BP was 0.69 (P < 0.01). ANN-assisted CIDI was compared with expert system assisted CIDI (kappa = 0.72-0.76); ANN was more powerful than a traditional expert system. CONCLUSION: ANN might be used to improve psychiatric diagnosis.

Adult↗

PubMed1987

Computer assisted psychiatric diagnosis: experiments in software design.

The process of psychiatric diagnosis involves the real-time utilization of large amounts of knowledge to maintain and test multiple hypotheses. Therefore, the development of an on-line computerized assistant that can aid a clinician performing psychiatric diagnoses presents challenging problems in data-base organization and retrieval. We have developed the DUNE (Diagnostic Understanding of Natural Events) system architecture that organizes the knowledge around processing structures. The system was designed as a shell for expert-systems that aid diagnoses and assessment tasks in ill-structured domains in general. These domains have previously proven unfeasible for traditional expert-systems such as rule based systems. Currently, DUNE contains sufficient knowledge to aid the diagnosis of anxiety and affective disorders. Among DUNE's advantages: a large degree of tolerance to clinician errors, and flexibility at run time. In this paper, we discuss the general specifications for a program that can aid psychiatric diagnoses, and then describe DUNE and its capabilities.

Adolescent↗

PubMed1993

Classification of endometriosis.

A perfect endometriosis classification should be a common language and an expert system which helps the gynaecologist to decide the treatment of each patient. The staging of endometriosis is not a new idea; the first classification based on histologic criteria was presented in 1941. Since this initial attempt, several classifications have been proposed. These various systems are reviewed in terms of their advantages and defects. The revised American Fertility Society (AFS) endometriosis classification system is now accepted worldwide as the endometriosis international language. Laparoscopic staging and measurement techniques are presented and discussed. In recent reports, changes to the revised AFS classification have been proposed, including a better description of atypical and deep infiltrating peritoneal implants, and a stage V for patients with bilateral, extensive, dense adhesions. Despite its well-known advantages, the revised AFS classification cannot be used as a satisfactory expert system. A better understanding of endometriosis is required to improve the present system. Scientifically based scores for each lesion and a marker for disease 'activity' will be fundamental to a classification which will act as a valuable expert system and become the endometriosis classification of the twenty-first century.

Endometriosis↗

PubMed2004

Evolutionary design of a fuzzy classifier from data.

Genetic algorithms show powerful capabilities for automatically designing fuzzy systems from data, but many proposed methods must be subjected to some minimal structure assumptions, such as rule base size. In this paper, we also address the design of fuzzy systems from data. A new evolutionary approach is proposed for deriving a compact fuzzy classification system directly from data without any a priori knowledge or assumptions on the distribution of the data. At the beginning of the algorithm, the fuzzy classifier is empty with no rules in the rule base and no membership functions assigned to fuzzy variables. Then, rules and membership functions are automatically created and optimized in an evolutionary process. To accomplish this, parameters of the variable input spread inference training (VISIT) algorithm are used to code fuzzy systems on the training data set. Therefore, we can derive each individual fuzzy system via the VISIT algorithm, and then search the best one via genetic operations. To evaluate the fuzzy classifier, a fuzzy expert system acts as the fitness function. This fuzzy expert system can effectively evaluate the accuracy and compactness at the same time. In the application section, we consider four benchmark classification problems: the iris data, wine data, Wisconsin breast cancer data, and Pima Indian diabetes data. Comparisons of our method with others in the literature show the effectiveness of the proposed method.

Algorithms↗

PubMed2005

Alzheimer disease is substantially preventable in the United States -- review of risk factors, therapy, and the prospects for an expert software system.

Epidemiology studies, including both regional incidence and the analysis of specific risk factors for Alzheimer's disease indicate that substantial prevention of the disease, in the 50-70 percent range, is a practical possibility for the United States. Epidemiology has identified a rich diversity of specific prevention strategies relating to nutrition, dietary supplements, lifestyle, food and environmental toxins, and in some cases medication, many of which have a capacity to reduce Alzheimer's risk by 50 percent or more. The interaction of these risk factors with brain biology is increasingly understood. In contrast, therapeutic strategies for un-prevented Alzheimer's generally prove incapable of delaying disease progression by more than 3-11 months, because extensive brain cell death occurs even in preclinical or mild cases. A public health program aimed at prevention can be fashioned with expert software packages, based on already identified risk factors. Such statistical analysis should allow the prediction of individual and group Alzheimer's risks of sufficient power to instruct the formulation of lifestyle, nutritional and environmental programs to substantially reduce disease incidence. A less satisfactory but complementary alternative is very early disease detection with therapeutic strategies focused on retardation of brain cell death, so that the person dies of another cause before the disease is clinically manifested.

Alzheimer Disease↗

PubMed1995

A rule-based decision support application for laboratory investigations management.

The appropriate management of clinical laboratory requests in specialised clinical units often requires the adherence to pre-defined protocols. We evaluated the impact of a rule-based expert system for clinical laboratory investigations management in a pediatric liver transplantation unit of our hospital. After one year, we observed an overall reduction in laboratory resources consumption for transplanted patients (-27%) and a decrease in the percentage of "STAT" requested tests (-44%). The percentage of tests ordered in agreement with the protocols for those patients increased from 33% before the introduction of the expert system to 45% when the system was used. The system was perceived by the clinicians as increasing the overall benefits in use of clinical resources, improving the laboratory data management, and saving time for the execution of laboratory ancillary tasks.

Clinical Laboratory Information Systems↗

PubMed2001

What to do about mental disorder--help-seeking recommendations of the lay public.

OBJECTIVE: Sociocultural factors have been recognized as an important predictor in shaping help-seeking behaviour. METHOD: We investigated attitudes of the lay public toward help-seeking for mental disorders in a population survey (n = 1,564) conducted in the new Laender of Germany. After presenting a vignette depicting a person either with major depression or with schizophrenia (DSM-III-R), we inquired about help-seeking recommendations. employing a qualitative approach. RESULTS: The lay support system plays an significant role in initially dealing with mental disorders. However, help-seeking recommendation differed for depression and schizophrenia. In depression, support from the lay system was more often considered. In schizophrenia, public opinion favoured the expert system. If primary suggestions fail the expert system is clearly favoured regardless of the disorder in question. CONCLUSION: Lay public's opinion has to be taken into account of in mental health care planning to make services more acceptable to the consumer and their social network.

Adolescent↗

PubMed1994

School nurse's assistant expert screening system.

The School Nurse's Assistant is designed to aid the School Nurse by providing a diagnostic discovery tool that also educates the student through the use of multimedia. Response initiated questions focus on the most pertinent student risk factors: lifestyle choices such as alcohol, drugs, and sexual activity. Because the questions are patient driven, the student stays interested as only relevant questions are presented. The School Nurse's Assistant provides the school nurse with increased sociographic information, and delivers cost-effective information to high risk segments of the student population. The potential for successful intervention is dramatic.

Adolescent↗

PubMed2001

EASY--an Expert Analysis SYstem for interpreting database search outputs.

With the ever-increasing need to handle large volumes of sequence data efficiently and reliably, we have developed the EASY system for performing combined protein sequence and pattern database searches. EASY runs searches simultaneously and distils results into a concise 1-line diagnosis. By bringing together results of several different analyses, EASY provides a rapid means of evaluating biological significance, minimising the risk of inferring false relationships, for example from relying exclusively on top BLAST hits. The program has been tested using a variety of protein families and was instrumental in resolving family assignments in a major update of the PRINTS database.

Computational Biology↗