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[Clinical method of evaluating declined intelligence with aging and its application in traditional Chinese medicine research].

A practical program edited by BASIC was used in this test. The test included 7 indexes of fluid intelligence by using the method of talking between man and computer: speed of mental mathematic, digit-symbol, choice reaction time, counting visual number span, tracing reaction and recognition of meaningless figures. Through the principal component analysis and multiple stepwise regression techniques, the authors found out the mathematical model of the intelligence aging from 506 normal subjects and established a measuring system for the declined fluid intelligence and physiological age could be measured with the system. The correlation of the repetition of the test was 0.9528. This method was suitable for mental workers of 46-75 years old. The measured accuracy among the subjects of 50-70 years old was higher. The method was applied practically in clinical evaluation of the effects of traditional herbal medicines and Qigong on fluid intelligence with aging. Through the analysis of validity and reliability, it was proved that this method was suitable for geriatric research.

Age Factors↗

Role and use of expert systems within the clinical laboratory.

Artificial intelligence can be used, mainly in the form of knowledge based systems, for different parts of clinical laboratory activity. Most of the iterative tasks for control and validation, or for maintenance or repair of automated instruments can be assisted by specialized software. There are now specific programmes (i) for control and validation of the request, where the goal is to modify the requesting behaviour of the physician, using protocol driven requests and immediate feedback, incorporating simultaneously a check of test request redundancy, (ii) for helping in equipment trouble-shooting, (iii) for technical and biological validation because too many QC data are issued from large equipment to be checked and used properly by the technologist whilst the pathologist can be assisted for the final revision of reports and (iv) for assistance in the interpretation of laboratory reports, one of the most valuable aspects of the pathologist's participation in the patient care process.

Clinical Chemistry Tests↗

Consistency and reproducibility of attribute extraction by different machine learning systems.

Machine learning systems as tools for intelligent data analysis are used for extracting attributes relevant for prediction of defined outcomes. The aim of the paper was to compare two machine learning (ML) systems and propose method for intra- and inter-testing of consistency and reproducibility in attributes extracted from real dataset. See5 and FMLS extracted relevant attributes from real medical dataset. Comparison of results of both systems shows that: accuracy and sensitivity are nearly the same for both FMLS and See5 when FMLS was forced by attributes extracted by See5, and little bit lower when FMLS used its own extracted attributes; specificity is nearly the same for both FMLS and See5 when FMLS was forced by attributes extracted by See5, and much more higher when FMLS used its own extracted attributes; both of ML systems show intra-testing consistency and does not show any inter-testing consistency.

Artificial Intelligence↗

A real time control architecture for continuously managing patients in a care unit.

The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient's evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient's care (execution of tests, administration of drugs) from a plan, and to monitor the patient's state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.

Clinical Protocols↗

Dopamine D2 receptor and N-methyl-D-aspartate receptor 2B subunit genetic variants and intelligence.

The dopaminergic and glutamate systems have been implicated in cognitive function. We tested the associations between the dopamine D2 receptor (DRD2) and N-methyl-D-aspartate receptor 2B subunit (GRIN2B) gene variants and intelligence quotient (IQ). Subjects with the DRD2 A1/A1 genotype had a significantly higher mean performance IQ than A2/A2 carriers, while no significant differences in IQ scores were determined for the three GRIN2B genotype groups. These results suggest that genetic variants of the DRD2 gene may play a role in cognitive function. Considering the major role played by the dopaminergic system in general cognitive function, genetic variants of the dopamine receptors and those involved in metabolism and modulation of reuptake should be tested to improve gene-based prediction of general cognitive function.

Adult↗

Artificial intelligence--its use in nephrology.

Artificial intelligence techniques and expert systems are graduating from research laboratories to enter many human domains of activities. However, initial expectations of the seventies have been transformed with time to a more sober reality. Starting from examples in nephrology, this paper tries to give a balanced view of this new technology. Justification, indication and limitation of present expert systems are discussed as regards their possible goals. The respective roles of the experts and knowledge engineers are described. The need to integrate the artificial intelligence approach into present patient database management systems in order to build up expert database systems is evaluated.

Database Management Systems↗

Intelligence and individual differences in becoming neurally efficient.

Physiological approaches to human psychometric intelligence have shown a higher neural efficiency (i.e. less cortical activation) during cognitive performance in brighter subjects. The main aim of this study was to explore the relationship between intelligence and cortical activation patterns in the framework of the learning test concept. In 27 participants we assessed the topography and extent of cortical activation by means of event-related desynchronization (ERD) during reasoning tests in a pre-test--training--post-test design and related it to psychometric intelligence (measured by the German Leistungs-Prüf-System, LPS). Significant associations between intelligence and cortical activation patterns were exclusively found at anterior (frontal) recording sites, which corroborates the central role of the frontal lobe for higher-order cognitive functions. The hypothesized negative intelligence-activation correlation was observed only after the training, i.e. in the post-test, but not in the pre-test. More important, the decrease in cortical investment from pre-test to post-test correlated negatively with intelligence, indicating that the higher the subjects' general mental ability the larger the decrease in the amount of cortical activation. These findings suggest intelligence-related individual differences in becoming neurally efficient.

Adolescent↗

DPS--a computerised diagnostic problem solver.

The paper contains a short description of the DPS system which is a computerized diagnostic problem solver. The system is under development of the Research Institute of Medical Bionics in Bratislava, Czechoslovakia. Its underlying philosophy yields from viewing the diagnostic process as process of cognitive problem solving. The implementation of the system is based on the methods of Artificial Intelligence and utilisation of production systems and frame theory should be noted in this context. Finally a list of program modules and their characterisation is presented.

Diagnosis, Computer-Assisted↗

[Role of the implicit theories of intelligence in learning situations].

Most studies have tried to explain the school difficulties by analysing the intellectual factors that lead to school failure. However in addition to the instrumental capacities, authors also recognize the role played by other factors such as motivation. More specifically, the theory of achievement motivation aims to determine motivational factors involved in achievement situations when the students have to demonstrate their competencies. This paradigm attributes a central place to beliefs in order to explain children's behavior in academic situations. According to Dweck, it seems that beliefs about the nature of intelligence have a very powerful impact on behavior. These implicit theories of intelligence create a meaning system or conceptual framework that influences the individual interpretation of school situations. Thus, an entity theory of intelligence is the belief that intelligence is a fixed trait, a personal quality that cannot be changed. Students who subscribe to this theory believe that although people can learn new things, their underlying intelligence remains the same. In contrast, an incremental theory of intelligence is the belief that intelligence is a malleable quality that can increase through efforts. The identification of these two theories allows us to understand the cognition and behavior of individuals in achievement situations. Many studies carried out in the academic area show that students who hold an entity theory of intelligence (ie they consider intelligence like a stable quality) have a strong tendency to attribute their failures to a fixed trait. They are more likely to blame their intelligence for ne-gative outcomes and to attribute failures to their bad intellectual ability. In contrast, students who hold an incremental theory of intelligence (ie they consider intelligence as a malleable quality) are more likely to understand the same ne-gative outcomes in terms of specific factors: they attribute them to a lack of effort. This differential emphasis on traits versus specific mediators in turn fosters different reactions to negative events. Several studies have shown that entity theorists of intelligence are more likely than incremental theorists to react helplessly in the face of failure. They are not only more likely to make negative judgments about their intelligence from the failures, but also more likely to show negative affect and behaviors. This helpless response pattern is cha-racterized by a lack of persistence, and performance decrements. In contrast, incremental theorists, who focus more on behavioral factors (eg effort, problem-solving strategies) as causes of negative achievement outcomes, tend to act on these mediators. They try harder and develop better strategies and continue to work. Some authors have tendency to consider implicit theories of intelligence as a disposition or a stable dimension. But in the last few years, several studies showed that people's theories are not fixed traits; they are beliefs that may be influenced. These studies also suggested that students use the two types of beliefs and that the context determines the choice between the two types of theories. According to these authors, the psychological state of the student depends on dispositional factors but also on situational factors. Thus, several studies have tried to demonstrate that it is possible to modify experimentally implicit theories of intelligence and subsequent cognitions and behaviors by modifying situational factors. Several studies have demonstrated that it was possible to induce students to adopt one of the two theories of intelligence by presenting them a scientific article that compelling argued for either an entity or an incremental view of intelligence. The results showed that participants who had received the entity theory induction exhibited more evidence of a helpless reaction to failure. These studies show that some of the judgments and reactions associated with implicit theories can be experimentally induced by manipulating participant theories. However in the context of school difficulties, only few works have been conducted. We think that the model of the motivation of achievement would allow us to better understand maladjusted behaviors that engender failure and scholastic exclusion. In one study, reseachers have demonstrated that children with mental disorders are less likely than other children to hold an incremental theory of their intellectual abilities. Other studies have demonstrated that entity theorists interpret their bad results according to their global intelligence level by negatively judging their global abilities ("I think I am stupid"). It is interesting to note that these students make the same attributions as depressive students. These results reveal the need to determine systems of beliefs within populations with anxiety or depressive symptoms in order to characterise their motivational profiles. Indeed, we think that these symptoms contribute to modify implicit theories of intelligence and the nature of the subsequent scholastic achievement. Finally, we think that it is inte-resting to demonstrate the positive motivational effects of the experimental induction of the incremental theory. A series of studies showed that children's theories of intelligence expe-rimentally induced will influence their tendency to persevere in the face of failure. Like normally developing children, children with mental disorders were more likely to prefer challenging activities and report high levels of interest-enjoyment when the task was presented as one which is improvable. It suggests that although children with difficulties are pessimistic about improving their intellectual capacities, if a new task is introduced in a way that highlights the possibility of self-improvement (incremental theory), then they will pursue the challenge in an adaptive manner (strong perseverance, enjoy, and important interest). These results are very inte-resting. Indeed, highlighting an incremental theory had a po-sitive motivational effect on behavior in achievement situations. In addition, all these results also may open up several interesting perspectives for the treatment of learning disabi-lities. The results should lead to plan programmes of cognitive therapy in order to modify beliefs that underlie maladjusted achievement behaviors of children and adolescents in scholastic failure.

Achievement↗

[A novel biologic electricity signal measurement based on neuron chip].

Neuron chip is a multiprocessor with three pipeline CPU; its communication protocol and control processor are integrated in effect to carry out the function of communication, control, attemper, I/O, etc. A novel biologic electronic signal measurement network system is composed of intelligent measurement nodes with neuron chip at the core. In this study, the electronic signals such as ECG, EEG, EMG and BOS can be synthetically measured by those intelligent nodes, and some valuable diagnostic messages are found. Wavelet transform is employed in this system to analyze various biologic electronic signals due to its strong time-frequency ability of decomposing signal local character. Better effect is gained. This paper introduces the hardware structure of network and intelligent measurement node, the measurement theory and the signal figure of data acquisition and processing.

Electrocardiography↗

On conceptualization of a decision support system in health informatics.

A decision support system can be approached from two major disciplinary perspectives, those of information systems science (IS) and artificial intelligence (AI). We present in this study an extended ontology for a decision support system in health informatics, which is founded on experience from related research fields as well as being informed by our case studies. The ontology emphasises the need to cover environmental and contextual variables as an integral part of a decision support systems development methodology. With the addition of these variables, the focus in decision support systems development shifts from a task ontology towards a domain ontology. The results of this study help the system developers to take the system's context into account through the set of defined variables that are linked to the application domain. These variables explicate relevant constructs and present a vocabulary for a decision support system. However, applying the ontology requires a more thorough analysis of the domain and therefore more qualified resources for systems development. This indicates the need to focus more on education and training in health informatics.

Artificial Intelligence↗

Meta-manager: a requirements analysis.

The digital imaging network-picture-archiving and communications system (DIN-PACS) will be implemented in ten sites within the Great Plains Regional Medical Command (GPRMC). This network of PACS and teleradiology technology over a shared T1 network has opened the door for round the clock radiology coverage of all sites. However, the concept of a virtual radiology environment poses new issues for military medicine. A new workflow management system must be developed. This workflow management system will allow us to efficiently resolve these issues including quality of care, availability, severe capitation, and quality of the workforce. The design process of this management system must employ existing technology, operate over various telecommunication networks and protocols, be independent of platform operating systems, be flexible and scaleable, and involve the end user at the outset in the design process for which it is developed. Using the unified modeling language (UML), the specifications for this new business management system were created in concert between the University of Arizona and the GPRMC. These specifications detail a management system operating through a common object request brokered architecture (CORBA) environment. In this presentation, we characterize the Meta-Manager management system including aspects of intelligence, interfacility routing, fail-safe operations, and expected improvements in patient care and efficiency.

Arizona↗

Expert systems in medicine.

The emergence of the artificial intelligence (AI) in computer technology and its application in the medical field enables the researchers to carry out such intelligent activities like image processing, medical reasoning systems, clinical decision supporting and natural language understanding, etc. A gastroenterological expert system application is briefly demonstrated in this paper. Similar expert systems can be seen to be useful in the research of gastrointestinal cytoprotection, including the plan of different compounds with cytoprotective effect, experimental and clinical medical research.

Decision Making, Computer-Assisted↗

Information, intelligence, and interface: the pillars of a successful medical information system.

This paper addresses three key issues facing developers of clinical and/or research medical information systems. 1. INFORMATION. The basic function of every database is to store information about the phenomenon under investigation. There are many ways to organize information in a computer; however only a few will prove optimal for any real life situation. Computer Science theory has developed several approaches to database structure, with relational theory leading in popularity among end users [8]. Strict conformance to the rules of relational database design rewards the user with consistent data and flexible access to that data. A properly defined database structure minimizes redundancy i.e.,multiple storage of the same information. Redundancy introduces problems when updating a database, since the repeated value has to be updated in all locations--missing even a single value corrupts the whole database, and incorrect reports are produced [8]. To avoid such problems, relational theory offers a formal mechanism for determining the number and content of data files. These files not only preserve the conceptual schema of the application domain, but allow a virtually unlimited number of reports to be efficiently generated. 2. INTELLIGENCE. Flexible access enables the user to harvest additional value from collected data. This value is usually gained via reports defined at the time of database design. Although these reports are indispensable, with proper tools more information can be extracted from the database. For example, machine learning, a sub-discipline of artificial intelligence, has been successfully used to extract knowledge from databases of varying size by uncovering a correlation among fields and records[1-6, 9]. This knowledge, represented in the form of decision trees, production rules, and probabilistic networks, clearly adds a flavor of intelligence to the data collection and manipulation system. 3. INTERFACE. Despite the obvious importance of collecting data and extracting knowledge, current systems often impede these processes. Problems stem from the lack of user friendliness and functionality. To overcome these problems, several features of a successful human-computer interface have been identified [7], including the following "golden" rules of dialog design [7]: consistency, use of shortcuts for frequent users, informative feedback, organized sequence of actions, simple error handling, easy reversal of actions, user-oriented focus of control, and reduced short-term memory load. To this list of rules, we added visual representation of both data and query results, since our experience has demonstrated that users react much more positively to visual rather than textual information. In our design of the Orthopaedic Trauma Registry--under development at the Carolinas Medical Center--we have made every effort to follow the above rules. The results were rewarding--the end users actually not only want to use the product, but also to participate in its development.

Artificial Intelligence↗

An intelligent rapid odour recognition model in discrimination of Helicobacter pylori and other gastroesophageal isolates in vitro.

Two series of experiments are reported which result in the discrimination between Helicobacter pylori and other bacterial gastroesophageal isolates using a newly developed odour generating system, an electronic nose and a hybrid intelligent odour recognition system. In the first series of experiments, after 5 h of growth (37 degrees C), 53 volatile 'sniffs' were collected over the headspace of complex broth cultures of the following clinical isolates: Staphylococcus aureus, Klebsiella sp., H. pylori, Enterococcus faecalis (10(7) ml(-1)), Mixed infection (Proteus mirabilis, Escherichia coli, and E. faecalis 3 x 10(6) ml each) and sterile cultures. Fifty-six normalised variables were extracted from 14 conductive polymer sensor responses and analysed by a 3-layer back propagation neural network (NN). The NN prediction rate achieved was 98% and the test data (37.7% of all data) was recognised correctly. Successful clustering of bacterial classes was also achieved by discriminant analysis (DA) of a normalised subset of sensor data. Cross-validation identified correctly seven 'unknown' samples. In the second series of experiments after 150 min of microaerobic growth at 37 degrees C, 24 volatile samples were collected over the headspace of H. pylori cultures in enriched (HPP) and normal (HP) media and 11 samples over sterile (N) cultures. Forty-eight sensor parameters were extracted from 12 sensor responses and analysed by a 3-layer NN previously optimised by a genetic algorithm (GA). GA-NN analysis achieved a 94% prediction rate of 'unknown' data. Additionally the 'genetically' selected 16 input neurones were used to perform DA-cross validation that showed a clear clustering of three groups and reclassified correctly nine 'sniffs'. It is concluded that the most important factors that govern the performance of an intelligent bacterial odour detection system are: (a) an odour generation mechanism, (b) a rapid odour delivery system similar to the mammalian olfactory system, (c) a gas sensor array of high reproducibility and (d) a hybrid intelligent model (expert system) which will enable the parallel use of GA-NNs and multivariate techniques.

Culture Media↗

The value of intelligent multimedia simulation for teaching clinical decision-making skills.

This paper examines the value of using intelligent multimedia simulation for the teaching of nursing clinical decision-making skills. The possibilities of multimedia-based educational resources are examined and the rapid growth and questionable effectiveness of current multimedia computer-based learning applications for nursing students are discussed. The advantages and disadvantages of this technology and the problems developing intelligent agent-based systems are examined. A case study is presented which uses a modular design with an integrated intelligent agent and knowledge base. It is argued that by using this type of approach, the real value of intelligent CBL to provide individual formative advice to students in a simulated experience can be realized.

Computer-Assisted Instruction↗