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PubMed1999

A software agent model of consciousness.

Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called "Conscious" Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological "facts that any complete theory of consciousness must explain" in his appendix to In the Theater of Consciousness; global workspace theory was designed to explain these "facts." The present article discusses how the design of CMattie accounts for these facts and thereby the extent to which it implements global workspace theory.

Cognition↗
PubMed2000

In defense of representation.

The computational paradigm, which has dominated psychology and artificial intelligence since the cognitive revolution, has been a source of intense debate. Recently, several cognitive scientists have argued against this paradigm, not by objecting to computation, but rather by objecting to the notion of representation. Our analysis of these objections reveals that it is not the notion of representation per se that is causing the problem, but rather specific properties of representations as they are used in various psychological theories. Our analysis suggests that all theorists accept the idea that cognitive processing involves internal information-carrying states that mediate cognitive processing. These mediating states are a superordinate category of representations. We discuss five properties that can be added to mediating states and examine their importance in various cognitive models. Finally, three methodological lessons are drawn from our analysis and discussion.

Cognition↗
PubMed1996

Similarity and complementarity of molecular shapes: applicability of a topological analysis approach.

Developments based on a topological analysis approach of electron density maps are presented and applied to two different fields: the interpretation of electron density maps of proteins and the description of shape complementarity between a cyclodextrin host and a guest molecule. A global representation of the electron density distribution, through the location, identification and linkage of its critical points (points where the gradient of the density vanishes, i.e., peaks and passes), is generated using the program ORCRIT. On one hand, the interpretation of protein electron density maps is based on similarity evaluations between graphs of critical points and known structures. So far, the method has been applied to 3 A resolution maps for the recognition of secondary structure motifs using a procedure relevant to expert systems in artificial intelligence. Satisfying matches between critical point graphs and their corresponding protein structure depict the ability of the topological analysis to catch the essential secondary structural features in electron density maps. On the other hand, mapping the accessible volume of a host molecule is achieved by representing the peaks as ellipsoids with axes related to local curvature of the electron density function. Related energies of the interacting species can also be estimated. A qualitative comparison is made between the results generated by the topological analysis and energy values obtained by conventional molecular mechanics calculations. A positive comparison and a close complementarity between cyclodextrin and ligands shows that the topological analysis method gives a good representation of the electron density function.

Computer Simulation↗
PubMed1990

Automated conformational analysis: algorithms for the efficient construction of low-energy conformations.

The method of constructing low-energy conformations using template joining can provide an efficient means of searching the conformational space of molecules. The simplest algorithm to perform this task would construct each potential conformation from scratch. However, new algorithms, some of which use techniques from Artificial Intelligence, have been developed which can greatly improve the efficiency of this approach.

Algorithms↗
PubMed1992

"Live" neuron and optimal learning rule.

A concept of the live unit as an automatic regulation system with a few admissible states areas in the space of states is considered. Energetic profit of oscillatory behavior consisting in the consecutive transitions of system from one admissible states area to another is shown. It is stated, that external disturbances cause the energy consumption of oscillatory system to decrease. On the basis of this concept and some neurophysiological data, the "live" energy-consuming nonlinear three-state neuron model is proposed and the existence of energy optimal generation frequency v(opt) is proved. For the realization of tendency to v(opt) the optimal learning rule is proposed, which provides unsupervised learning and interlinked short-term and long-term memories with forgetting. The model proposed explains the genesis of neural network, is promising in the sense of network self-organization and allows to solve the problem of internal activity in the researches on artificial intelligence.

Biological Clocks↗
PubMed1988

Spontaneous subarachnoid haemorrhage: expert system for appraisal of the prognosis and computer-supported decision for therapy.

An expert system is presented which allows appraisal of the prognosis and a computer-supported decision for the therapy of patients with acute spontaneous subarachnoid haemorrhage (SAH). The knowledge of physicians as a synthesis of their own and other clinicians' experience is simulated with methods of artificial intelligence by setting up two data banks. In one data bank, selected information on the correlation between initial clinical parameters, on the one hand, and mortality, outcome and complications, on the other, from about 250 neurological publications is stored, taking into consideration the therapeutic regimens applied. A second data bank receives clinical and laboratory data profiles of a patient population which has already been treated. The expert system is able to compare the individual initial findings with the corresponding parameter combination stored in the data banks regarding the decision for therapy of a patient to be treated. This enables both calculation of the probable complications and prediction of the expected outcome in relation to various possible forms of therapy. The expert system can thus indicate the kind of therapy where the lowest number of complications and the best outcome can be expected, thus supporting the decision of the physician. As each new patient is treated, the volume of stored information increases, so the system possesses self-learning characteristics. To check the validity of the prognoses, the outcome estimated by the expert system for 51 patients with spontaneous SAH was compared with the actual outcome, and a high level of agreement was attained.

Decision Making, Computer-Assisted↗
PubMed1985

An expert system for nursing practice. Clinical decision support.

An artificial-intelligence-based nursing knowledge base can serve as an expert clinical decision support system in the areas of standards of care, care plans, continuing education, and others for patient conditions with both medical and nursing diagnoses.

Computers↗
PubMed1983

AI/RHEUM. A consultant system for rheumatology.

A knowledge-based computer consultant system in the medical specialty area of rheumatology is described. The system, called AI/RHEUM, uses artificial intelligence techniques to provide nonrheumatologist physicians with diagnostic assistance in this specialty area. AI/RHEUM contains in a structured knowledge base formal criteria for 26 rheumatologic diseases. The system has been retrospectively tested against 384 clinical cases, with an overall correct diagnostic performance of 94%.

Computers↗
PubMed1989

Reporting results from a clinical pharmacological laboratory using a microcomputer.

Responsibility lies with an analytical pharmacological laboratory to issue each result with an assessment of its validity for the corresponding patient. This is scarcely possible by the usual manual methods of data handling even when complete diagnostic and pharmacokinetic data are available, because of the staff time required. Use of a microcomputer running a suite of True Basic programs showing "artificial intelligence" solves the temporal difficulty and leads to the issue of more incisive, detailed reports.

Clinical Laboratory Information Systems↗
PubMed1994

Automated extraction, labelling and analysis of the coronary vasculature from arteriograms.

For clinical decision-making and documentation purposes we have developed techniques to extract, label and analyze the coronary vasculature from arteriograms in an automated, quantitative manner. Advanced image processing techniques were applied to extract and analyze the vasculatures from non-subtracted arteriograms while artificial intelligence techniques were employed to assign anatomical labels. Lumen diameters of 11 phantom vessels were assessed with an accuracy of 0.27 +/- 0.19 mm (dtrue = 0.45 + 0.92dmeasured; r > 0.99) and 0.21 +/- 0.15 mm (dtrue = 0.42 + 0.91dmeasured; r > 0.99), from cine and digital images, respectively. We collected a total of 15 routinely acquired cine-arteriograms showing 74 vessel segments with 18 stenoses (severity larger than 30% assessed quantitatively), and 53 digital arteriograms showing 236 vessel segments with 69 stenoses. From the cine arteriograms we extracted 64 (86%) of the vessel segments without manual correction and 196 (83%) from the digital arteriograms. Repeated analysis (3 times) of the arteriograms by the same operator resulted in a standard deviation of the mean segment diameters (precision) of 0.064 mm for the cine-images and 0.020 mm for the digital images, while the standard deviations in the measurement of the minimal luminal diameter of the observed stenoses were 0.020 mm and 0.019 mm, respectively. The LAD artery, the septal and diagonal branches were correctly identified automatically in 86% of the segments. From these evaluations we conclude that our automated approach provides reliable tools for the assessment of multi-vessel disease, both in an off- and on-line environment.

Cineangiography↗
PubMed1992

A demonstration that breast cancer recurrence can be predicted by neural network analysis.

Neural Network Analysis, a form of artificial intelligence, was successfully used to predict the clinical outcome of node-positive breast cancer patients. A Neural Network was trained to predict clinical outcome using prognostic information from 1008 patients. During training, the network received as input information tumor hormone receptor status, DNA index and S-phase determination by flow cytometry, tumor size, number of axillary lymph nodes involved with tumor, and age of the patient, as well as length of clinical followup, relapse status, and time of relapse. The ability of the trained Network to determine relapse probability was then validated in a separate set of 960 patients. The Neural Network was as powerful as Cox Regression Modeling in identifying breast cancer patients at high and low risk for relapse.

Axilla↗
PubMed1991

The role of medicinal chemistry in drug research.

Classical medicinal chemistry, that is molecular modifications of existing bioactive compounds, leading to me-too drugs with value added and often to me-too drugs which will never reach the market or to drugs in another pharmacological field than that originally intended, will be with us for a long time to come. The ultimate goal, however, is of course rational or at least semi-rational drug design. In some instances this goal seems to have already been reached as in the case of angiotensin-converting enzyme inhibitors and H2 antagonists. In the (near) future results from the steady progress in molecular biology in combination with computer-assisted drug modelling--possibly coupled with artificial intelligence techniques--will help the medicinal chemist in his efforts to attain this goal.

Animals↗
PubMed1984

Implementation of a computer-based test generator to evaluate health professions continuing education.

A variety of artificial-intelligence-based expert medical systems have been adapted to evaluate a learner's performance in the information areas in which the systems are expert. This paper describes a similar adaptation of a computer-based health sciences tutor (called the COMMES system). The Evaluation Consultant system to be described adapts the COMMES system to become a test generator. This computer-based consultant generates tests entirely on its own, covering programs of study that the COMMES system previously constructed to satisfy a user's identified needs. A health professional is awarded continuing education credits after (1) finishing a study unit constructed by COMMES and (2) completing successfully a test created by the Evaluation Consultant. This system is being implemented in several test sites and has significant advantages for the support of continuing education, especially in rural or isolated areas.

Computer-Assisted Instruction↗
PubMed1984

A comparison of LISP and MUMPS as implementation languages for knowledge-based systems.

Major components of knowledge-based systems are summarized, along with the programming language features generally useful in their implementation. LISP and MUMPS are briefly described and compared as vehicles for building knowledge-based systems. The paper concludes with suggestions for extensions to MUMPS that might increase its usefulness in artificial intelligence applications without affecting the essential nature of the language.

Computers↗
PubMed1999

Reliability of neural-network functional electrical stimulation gait-control system.

Functional electrical stimulation (FES) has been used for restoring walking in spinal-cord injured (SCI) persons. Using artificial intelligence (AI), FES controllers have been developed that allow the automatic phasing of stimulation, to replace the function of hand or heel switches. However, there has been no study to evaluate the reliability of these AI systems. Neural networks were used to construct FES controllers to control the timing of stimulation. Different numbers of sensors in the sensor set and different numbers of data points from each sensor were used. Two incomplete-SCI subjects were recruited, and each was tested on three separate occasions. The results show the neural-network controllers can maintain a high accuracy (around 90% for the two- and three-sensor groups and 80% for the one-sensor group) over a period of six months. Two or three sensors were sufficient to provide enough information to construct a reliable FES control system, and the number of data points did not have any effect on the reliability of the system.

Adult↗
PubMedDate not supplied

Neural networks in the study of the brain.

Neural networks are models of the brain and have been used within Artificial Intelligence to provide alternative explanations to the symbolic explanations of cognition in which one assumes that an intelligent system has certain explicit representation of some aspect of the world and uses these in intelligent behavior. Obviously, if neural networks are indeed good models of the brain, and give a satisfactory account of cognition, then they could be a valuable tool to neuroscientists. This article gives a brief overview of the various neural network models, and critically reviews their status as models of the brain and of cognition.

Animals↗
PubMed1989

Structure characteristics of QMSOC and the relevant operators.

This article presents a further description on the background, significance, and structure characteristics of Quantitative Medicine Simulation and Operation by Computer (QMSOC). Also some basic operators were recommended for calculations of biomedical events such as estimation of substance concentrations, exploration of etiology, evaluation of biomedical effects, etc. At last some differences of QMSOC from other artificial intelligent systems in the medical field were discussed.

Computer Simulation↗
PubMed2003

Automatic prediction of protein function.

Most methods annotating protein function utilise sequence homology to proteins of experimentally known function. Such a homology-based annotation transfer is problematic and limited in scope. Therefore, computational biologists have begun to develop ab initio methods that predict aspects of function, including subcellular localization, post-translational modifications, functional type and protein-protein interactions. For the first two cases, the most accurate approaches rely on identifying short signalling motifs, while the most general methods utilise tools of artificial intelligence. An outstanding new method predicts classes of cellular function directly from sequence. Similarly, promising methods have been developed predicting protein-protein interaction partners at acceptable levels of accuracy for some pairs in entire proteomes. No matter how difficult the task, successes over the last few years have clearly paved the way for ab initio prediction of protein function.

Computational Biology↗