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PubMed1988

[Systems assisting decisions in clinical medicine].

There are numerous systems and computerized procedures which have been developed and tested as a guide to clinical decisions. The methods used in the development of these systems can be divided into two large groups: mathematical and logical. None of these can be considered as better than the other in absolute, but the efficiency of each system depends on that problem is to be described and solved. The mathematical methods seem more suitable in the description of biological systems and for the selection of groups which have discriminant and sufficiently defined characteristics. Meanwhile the logical methods are better in the description and the formalization of more complicated clinical problems, characterized by uncertainty and availability of more or less numerous alternatives. It is foreseen that in the next years the systems for aided decision making will be programmed making use of methods belonging to both categories, and particularly, the expert systems will be planned using both artificial intelligence techniques and mathematical and statistical methods. The increasing frequency in the use of such systems in clinical practice will cause a reevaluation and a checking of most aspects of medical proceedings, as seen by the new methodologies or the traditional methods whose use could be driven by computer.

Algorithms↗
PubMed1983

The heat resistance of a data-encoded ceramic microchip identification system.

Samis introduced the concept of the Dentify system of personal identification. In this system, ceramic microchips embossed with metallic intelligence data are placed in teeth under dental restorations. This paper describes the results of an in vitro study aimed at testing the heat resistance qualities of this identification system when placed in teeth. Teeth were subjected to a temperature of 1,000 degrees C. The results of this study indicate that the ceramic chips and their embossed metallic intelligence data are able to withstand extremely high temperatures. The metallic identifier pins used in this study were less resistant to extreme heat. The significance of these findings is discussed.

Ceramics↗
PubMed1993

Development of an expert system for pediatric auditory brainstem response interpretation.

Expert systems are computer programs which incorporate artificial intelligence technology and are created to emulate the decision-making abilities of human experts. The advantage of such systems lies in their ability to capture and model expert problem solving knowledge in a domain and make it available to an unlimited number of consumers in an economic and efficient way. The purpose of this project was to develop an expert system to interpret infant auditory brainstem response data as entered by the user. The resulting system provides diagnostic conclusions regarding hearing status, type of hearing loss, and brainstem function at an accuracy level equal to that of a human expert.

Artificial Intelligence↗
PubMed2001

An application of artificial neural intelligence for personal dose assessment using a multi-area OSL dosimetry system.

Significant advances have been made in recent years to improve measurement technology and performance of phosphor materials in the fields of optically stimulated luminescence (OSL) dosimetry. Pulsed and continuous wave OSL studies recently carried out on alpha-Al2O3:C have shown that the material seems to be the most promising for routine application of OSL for dosimetric purposes. The main objective of the study is to propose a new personal dosimetry system using alpha-Al2O3:C by taking advantage of its optical properties and energy dependencies. In the process of the study, a new dose assessment algorithm was developed using artificial neural networks in hopes of achieving a higher degree of accuracy and precision in personal OSL dosimetry system. The original hypothesis of this work is that the spectral information of X- and gamma-ray fields may be obtained by the analysis of the response of a multi-element system. In this study, a feedforward neural network using the error back-propagation method with Bayesian optimization was applied for the response unfolding procedure. The validation of the proposed algorithm was investigated by unfolding the 10 measured responses of alpha-Al2O3:C for arbitrarily mixed photon fields which range from 20 to 662 keV.

Algorithms↗
PubMed1998

Intelligent computer reporting 'lack of experience': a confidence measure for decision support systems.

The purpose of this study was to explore the feasibility of developing artificial neural networks that are able to provide confidence measures for their diagnostic advice. Computer-aided decision making can improve physician performance, but many physicians hesitate to use these 'black boxes'. If we are to rely upon decision support systems for such tasks as medical diagnosis it is essential that the computers indicate when the advice given is based on experience, i.e. give a confidence measure. An artificial neural network was trained to diagnose healed anterior myocardial infarction and to indicate 'lack of experience' when test electrocardiograms were different from the electrocardiograms of the training set. A database of 1249 electrocardiograms from patients who had undergone cardiac catheterization was used to train and test the neural network. Thereafter, the ability of the network to indicate 'lack of experience' was assessed using 100 left bundle branch block electrocardiograms, an electrocardiographic pattern that was excluded from the training set. The network indicated that 83% of the left bundle branch block electrocardiograms and 1% of the test electrocardiograms from catheterized patients were different from the electrocardiograms of the training set. All but one of the left bundle branch block electrocardiograms would otherwise be falsely classified as anterior myocardial infarction by the network. Artificial neural networks can be trained to indicate 'lack of experience', and this ability increases the possibility for neural networks to be accepted as reliable decision support systems in clinical practice.

Bundle-Branch Block↗
PubMed2004

A knowledge-based framework for image enhancement in aviation security.

The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

Algorithms↗
PubMed2004

A minimal axiom group for rough set based on quasi-ordering.

Rough set axiomatization is one aspect of rough set study to characterize rough set theory using dependable and minimal axiom groups. Thus, rough set theory can be studied by logic and axiom system methods. The classic rough set theory is based on equivalent relation, but rough set theory based on reflexive and transitive relation (called quasi-ordering) has wide applications in the real world. To characterize topological rough set theory, an axiom group named RT, consisting of 4 axioms, is proposed. It is proved that the axiom group reliability in characterizing rough set theory based on similar relation is reasonable. Simultaneously, the minimization of the axiom group, which requires that each axiom is an equation and each is independent, is proved. The axiom group is helpful for researching rough set theory by logic and axiom system methods.

Algorithms↗
PubMed1997

[Expert systems for medicine--functions and developments].

Medical knowledge doubles every five years. Electronic media are necessary to manage these volumes. "Multimedia" and "information highway" are buzz-words and also concern medicine. Medical informatics tries to build a bridge between medical research which generates knowledge and daily practice in hospitals, ambulatory care and public services. Knowledge is used in different representations for multiple purposes and functions. Expert systems are mostly designed to fulfil certain functions and to support routine clinical practice. This paper tries to point out some important functions and to explain the capabilities by means of two example systems which can be used in several medical units. The main problem in using expert systems is, besides the quality of knowledge, the availability of patient data. For this reason the existence of an electronic patient record is another area which will be described in this paper. Expert systems are specialised medical information systems and have to fulfil the same success criteria as all the other systems, e.g. the integration into the daily routine as a trusted tool.

Adult↗
PubMedDate not supplied

Utility of the PASS theory and cognitive assessment system for Dutch children with and without ADHD.

This study examined the utility of the Planning, Attention, Simultaneous, Successive (PASS) theory of intelligence as measured by the Cognitive Assessment System (CAS) for evaluation of children with attention-deficit/hyperactivity disorder (ADHD). The CAS scores of 51 Dutch children without ADHD were compared to the scores of a group of 20 Dutch children with ADHD. The scores of the Dutch children were also compared to American standardization samples of children with and without ADHD. The findings showed that children with ADHD in both countries demonstrated relatively low scores on the Planning and Attention scales of the CAS, but average scores on the Simultaneous and Successive scales. These findings are similar to previously published research suggesting that the PASS theory, as operationalized by the CAS, has sensitivity to the cognitive processing difficulties found in some children with ADHD.

Attention Deficit Disorder with Hyperactivity↗
PubMedDate not supplied

An object-based architecture for biomedical expert database systems.

Objects play a major role in both database and artificial intelligence research. In this paper, we present a novel architecture for expert database systems that introduces an object-based interface between relational databases and expert systems. We exploit a semantic model of the database structure to map relations automatically into object templates, where each template can be a complex combination of join and projection operations. Moreover, we arrange the templates into object networks that represent different views of the same database. Separate processes instantiate those templates using data from the base relations, cache the resulting instances in main memory, navigate through a given network's objects, and update the database according to changes made at the object layer. In the context of an immunologic-research application, we demonstrate the capabilities of a prototype implementation of the architecture. The resulting model provides enhanced tools for database structuring and manipulation. In addition, this architecture supports efficient bidirectional communication between database and expert systems through the shared object layer.

Database Management Systems↗
PubMed2006

How do experts recognize schizophrenia: the role of the disorganization symptom.

OBJECTIVE: Research on clinical reasoning has been useful in developing expert systems. These tools are based on Artificial Intelligence techniques which assist the physician in the diagnosis of complex diseases. The development of these systems is based on a cognitive model extracted through the identification of the clinical reasoning patterns applied by experts within the clinical decision-making context. This study describes the method of knowledge acquisition for the identification of the triggering symptoms used in the reasoning of three experts for the diagnosis of schizophrenia. METHOD: Three experts on schizophrenia, from two University centers in Sao Paulo, were interviewed and asked to identify and to represent the triggering symptoms for the diagnosis of schizophrenia according to the graph methodology. RESULTS: Graph methodology showed a remarkable disagreement on how the three experts established their diagnosis of schizophrenia. They differed in their choice of triggering-symptoms for the diagnosis of schizophrenia: disorganization, blunted affect and thought disturbances. CONCLUSIONS: The results indicate substantial differences between the experts as to their diagnostic reasoning patterns, probably under the influence of different theoretical tendencies. The disorganization symptom was considered to be the more appropriate to represent the heterogeneity of schizophrenia and also, to further develop an expert system for the diagnosis of schizophrenia.

Decision Support Systems, Clinical↗
PubMedDate not supplied

Decision support for drug prescription integrated with computer-based patient records in primary care.

A conceptual model of an information system that integrates a controlled vocabulary, a patient database, and a knowledge base is described. Methods, design and components for the implementation of the system are discussed. It is argued that the key issue for the successful introduction of computer-based decision support in primary care today is integration with a computer-based patient record. Also important is that the knowledge acquisition process is based on the general practitioner's real needs. This has been achieved by, first, providing general practitioners with real patient data from a series of retrospective database studies; and second, letting a panel of general practitioners select, discuss and decide which computer reminders to implement. A hybrid representation scheme was chosen for the knowledge base. The combination of a standard procedural representation (the so-called Arden syntax) for the reminder knowledge with a semantic net representation for the medical factual knowledge facilitates knowledge sharing with other systems and knowledge reuse within the system.

Artificial Intelligence↗
PubMed1996

Object-oriented development of a concept learning system for time-centered clinical data.

A concept learning system is expected to be a powerful tool for filtering and analyzing a large amount of data in a variety of scientific fields. A simple application of it to clinical data, however, fails to mine medical information and knowledge. One of the major obstacles in mining a clinical database is time, which is a very important concept in clinical medicine. To be successful in data mining in clinical medicine, an efficient model of clinical data with time and a flexible concept learning system augmented to handle the model are both necessary. Herein we modeled clinical data to easily express and manipulate time and extended a concept learning system to utilize a time-centered clinical data model. The modified concept learning system is based on the message-value method rather than the traditional attribute-value method. The object-oriented technology was of great help in modeling time-centered clinical data and in developing a modified concept learning system.

Algorithms↗
PubMed1989

How important is histocompatibility in bone marrow transplantation?

The main issue addressed at the Fifth International Workshop on Bone Marrow Transplantation for Leukaemia was the importance of the major histocompatibility complex (MHC) and of minor histocompatibility (minor H) systems in allogeneic bone marrow transplantation (BMT) in humans. It is well established that mismatching for either HLA or minor antigens increases the risks of graft-versus-host disease (GVHD) and graft failure. In HLA-identical sibling transplants minor antigen differences may be responsible for these problems, which might be reduced by matching for minor antigens and improving methods for immunosuppression in vivo. If a suitable family member is not available, then a 'matched' unrelated donor (MUD) may be an alternative. At present MUD transplants have greater risks of GVHD and graft failure and consequently poor survival than HLA-identical sibling transplants; this may be due to unrecognized MHC polymorphisms or to multiple minor H differences. Possible strategies to improve the results of MUD transplants include better HLA matching, new in vitro functional tests for optimizing donor selection and better immunosuppression. Approaches for improving HLA typing include isoelectric focusing for class I and RFLP/allogenotyping or oligonucleotide typing for class II antigens. One obvious disadvantage of exploiting more precise methods for donor matching is the possibility of excluding donors with biologically unimportant histocompatibility differences, which would increase rather than reduce the proportion of patients without donors in a given panel. Functional assays could help in selecting donors on the basis of 'intelligent mismatching' within the HLA system.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1994

Fat and cholesterol in the diet of infants and young children: implications for growth, development, and long-term health.

Fat is necessary in the diets of infants and young children because of their extraordinary energy needs and limited dietary capacity. In addition, essential fatty acids provide the substrates for arachidonic acid, docosahexaenoic acid, and their metabolites. Deficiencies in the amounts of these long-chain fatty acids in the diet during infancy may affect the maturation of the central nervous system, including visual development and intelligence. Efforts to link the diet in infancy and early childhood to the development of chronic diseases in adulthood are hampered by a lack of supportive epidemiologic and clinical data. Serum cholesterol and lipid levels during childhood correlate only weakly with their levels at maturity. Studies in twins suggest that there is a large genetic component to serum lipid levels. Similarly, the correlation between obesity in early childhood and in adulthood is weak. Young children who receive fat-restricted diets in which fat accounts for 30% or less of their intake appear to grow normally but are more likely not to consume the recommended dietary allowances of many nutrients. Therefore fat should not be restricted in the diets of infants and young children. Restricting fat to approximately 30% of the calories consumed is reasonable after the age of 2 years, but the benefits of this recommendation remain to be proved.

Adult↗