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At least 1,153 records · Page 64Linked to original sources
PubMed2005

Cerebral lateralization and general intelligence: gender differences in a transcranial Doppler study.

The present study evaluated cerebral lateralization during Raven's progressive matrices (RPM) paradigm in female and male subjects. Bilateral simultaneous transcranial Doppler (TCD) ultrasound was used to measure mean blood flow velocities (MBFV) in the right and left middle cerebral arteries (MCAs) in 24 (15 females and 9 males) right-handed normal subjects. The female subjects used a left hemisphere strategy, while males used a right hemisphere strategy to successfully solve RPM tasks. This implies that general intelligence is associated with neural systems within one hemisphere that are accessible to a variety of cognitive processes.

Adult↗
PubMed2005

Artificial intelligence in hematology.

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Artificial Intelligence↗
PubMed2005

[Application of syntactic pattern recognition in research on pulse wave's characteristic information].

In this paper, a syntactic pattern recognition method of the detection of pulse wave's characteristic information is introduced. According to it, the pressure signal of pulse is measured by non-invasive diagnostic method. Then, the elementary abstracting system transfers it into an input pattern. The recognizer, constructed by Earley algorithm, recognizes the pulse wave's pattern. On the base of it, the pulse wave's characteristic information can be got. Thus, the expert system will make a diagnosis with the information. The experiment result shows that, the new method is of anti-interference, preciseness and intelligence, and it provides an advanced, practical and intelligent means for the pulse diagnostic system.

Algorithms↗
PubMed1999

Information and redundancy: key concepts in understanding the genetic control of health and intelligence.

A model is proposed in which information from the environment is analysed by complex biological decision-making systems which are highly redundant. A correct response is intelligent behaviour which preserves health; incorrect responses lead to disease. Mutations in genes which code for the redundant systems will accumulate in the genome and impair decision-making. The number of mutant genes will depend upon a balance between the new mutation rate per generation and systems of elimination based on synergistic interaction in redundant systems. This leads to a polygenic pattern of inheritance for intelligence and the common diseases. The model also gives a simple explanation for some of the hitherto puzzling aspects of work on the genetic basis of intelligence including the recorded rise in IQ this century. There is a prediction that health, intelligence and socio-economic position will be correlated generating a health differential in the social hierarchy. Furthermore, highly competitive societies will place those least able to cope in the harshest environment and this will impair health overall. The model points to a need for population monitoring of somatic mutation in order to preserve the health and intelligence of future generations.

Genetic Predisposition to Disease↗
PubMed1961

Cerebral dysfunction and intellectual impairment in old age.

There is a marked decline in some intellectual abilities in old age. It is frequently hypothesized that impaired cerebral physiology accounts for some of this deficit. In old age the critical flicker frequency, a measure sensitive to cerebral dysfunction, is correlated with aging intellectual abilities. This is interpreted as evidence supporting the above hypothesis.

Aging↗
PubMed2003

The role of soft computing in intelligent machines.

An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

Algorithms↗
PubMed2003

Bioscience and analytical thinking machines.

Is science being limited by the restricted vision of the analytical scientist? Adrian Stevenson from the Institute of Biotechnology at University of Cambridge argues that human 3D visualisation abilities to find patterns are inadequate and that artificial intelligence may hold the vital key to understanding information dense biological systems.

Animals↗
PubMed2005

The Systemic Theory of Living Systems and Relevance to CAM: The Theory (Part II).

This theory stems from observing the universe's 'omniscient' nature, manifested in flows of energy and information of its life plethora. A notorious example is the living cell's intelligent nature, which guides its basic goal: to maximize survival. This last motivated me to address the living system's intelligence, which constitutes a vital and controversial topic, its relationship with 'incurable' disease in general, including cancer, and to propose golden rules for therapeutics, as well as a definition of ideal medicine. The scientific confirmation of these findings is embedded in discoveries in cybernetics, biological theory of information and modern thermodynamic concepts, concerning energy and information exchange, within a living system. This approach's practical application, denominated Systemic Medicine, has been substantiated by treatment and results obtained in >300 000 patients suffering from chronic degenerative diseases.

Journal Article↗
PubMedDate not supplied

Protocols and guides, tools.

The author describes in the first part of the review the definitions and relations of the occurring concepts. In the second part a short history of the topic is overviewed. The third part is dealing with the electronic patient record based development of guidelines in addition what are the relations among guidelines, protocols, tools, knowledge-based systems, diagnosis supporting systems, expert systems, outcome analysis and artificial intelligence. A short review of what was presented in the MIE '97 in this area is finally described and the Session Chairman's conclusion.

Computer Communication Networks↗
PubMed2004

Safety of soy-based infant formulas containing isoflavones: the clinical evidence.

Soy protein has been used in infant feeding in the West for nearly 100 y. Soy protein infant formulas have evolved in this interval to become safe and effective alternatives for infants whose nutritional needs are not met with human milk or formulas based on cow's milk. Modern soy formulas meet all nutritional requirements and safety standards of the Infant Formula Act of 1980. They are commonly used in infants with immunoglobulin E-mediated cow's milk allergy (at least 86% effective), lactose intolerance, galactosemia, and as a vegetarian human milk substitute. Largely as a result of research in animal models, concerns have been voiced regarding isoflavones in soy infant formulas in relation to nutritional adequacy, sexual development, neurobehavioral development, immune function, and thyroid disease. We discuss the available clinical evidence regarding each of these issues. Available evidence from adult human and infant populations indicates that dietary isoflavones in soy infant formulas do not adversely affect human growth, development, or reproduction.

Animals↗
PubMed1998

Building cross-thesauri with the support of UMLS.

The absence of a robust system of descriptors (cross-thesaurus) hampers the development of combinatorial terminological systems. We developed a tool (I-BROWSE) to produce a cross-thesaurus by analyzing terminological corpora. To facilitate the work of experts and to produce re-usable results, our application interacts via the Internet with the UMLS Knowledge Sources Server. We applied our tool on 2999 dissections on surgical procedures produced in the project GALEN-IN-USE, as a part of the internal Quality Assurance program. Support from UMLS seems mostly promising about descriptors on , , and . Additional assistance can be given to domain experts on less frequent descriptors on pervasive modifiers. We plan to apply our tool also to production of terminological standards in CEN, as a part of a worldwide process of gradual convergence and transformation of coding systems into second-generation systems and terminological services.

Artificial Intelligence↗
PubMed2006

Overview: Computational analysis and decision support systems in oncology.

Computational analysis tools and decision support systems have increased their penetration in the support of clinical processes and management of medical data and knowledge. Applications range from adjunct tools for diagnosis and disease investigation to the treatment and monitoring of therapeutic procedures. As all medical fields, the field of oncology is affected. This special issue includes studies presenting research and applications of computational intelligence in oncology, covering four main areas: i) decision support systems (DSS) and artificial intelligence (AI) applications in oncology; ii) design and assessment of classification tools in oncology; iii) intelligent accessing, retrieving, and storing of medical images; and iv) intelligent telemedicine and telehealth applications in oncology.

Artificial Intelligence↗
PubMed2000

The phase diagram of the monoolein/water system: metastability and equilibrium aspects.

Interest in the liquid crystal structure, transport and membrane protein crystallizing properties of the monoolein/water system has grown in the recent past. Monoolein is also an important homolog in a series of monoacylglycerols used to decipher how lipid molecular structure relates to liquid crystal phase behavior--information needed for rational design applications and for understanding the origin of membrane lipid diversity. To make intelligent use of the monoolein/water system, a reliable and detailed temperature-composition phase diagram is needed. The phase diagram of Briggs et al. (J Phys II France 1996;6:723-51) was constructed for this purpose. However, we have established that the liquid crystal phases in the latter below ca. 20 degrees C are metastable. By implementing a sub-zero degree (degrees C) sample incubation prior to data collection in the heating direction, we can reset the system into the lamellar crystal phase which we assume represents equilibrium behavior. We have re-examined the low-temperature part of the phase diagram and characterized structurally the new 'equilibrium' phases by static and time-resolved low- and wide-angle X-ray diffraction and by differential scanning calorimetry. A more complete phase diagram that incorporates the new equilibrium behavior at low temperatures is reported.

Calorimetry, Differential Scanning↗
PubMed1998

Static cytometry and neural networks in the discrimination of lower urinary system lesions.

OBJECTIVES: To investigate the potential of morphometry and artificial intelligence tools for the discrimination of benign and malignant lower urinary system lesions. METHODS: The study group included 50 cases of lithiasis, 61 cases of inflammation, 99 cases of benign prostatic hyperplasia, 5 cases of in situ carcinoma, 71 cases of grade I transitional cell carcinoma of the bladder (TCCB), and 184 cases of grade II and grade III TCCB. Images of voided urine smears stained by the Giemsa technique were analyzed by a custom image analysis system. The analysis gave a data set of features from 45,452 cells. A learning vector quantizer (LVQ)-type neural network (NN) was used to discriminate benign from malignant cells on the basis of the extracted morphometric and textural features. The data from 13,636 randomly selected cells were used as a training set and the data from the remaining 31,816 cells made up the test set. Similarly, in an attempt to discriminate at the patient level, 30% of the cases randomly selected were used to train an LVQ NN and the remaining 329 cases were used for the test. RESULTS: The application of the LVQ NN enabled the correct classification of 95.42% of the benign cells and 86.75% of the malignant cells, giving an overall accuracy rate of 90.63%. At the patient level, the LVQ NN enabled the correct classification of 100% of benign cases and 95.6% of malignant cases, giving an overall accuracy rate of 97.57%. CONCLUSIONS: NNs combined with image analysis offer useful information in the discrimination of benign and malignant cells and lesions of the lower urinary system.

Diagnosis, Differential↗
PubMed2002

Putting intentions into cell biochemistry: an artificial intelligence perspective.

The living cell exists by virtue of thousands of nonlinearly interacting processes. This complexity greatly impedes its understanding. The standard approach to the calculation of the behaviour of the living cell, or part thereof, integrates all the rate equations of the individual processes. If successful extremely intensive calculations often lead the calculation of coherent, apparently simple, cellular "decisions" taken in response to a signal: the complexity of the behavior of the cell is often smaller than it might have been. The "decisions" correspond to the activation of entire functional units of molecular processes, rather than individual ones. The limited complexity of signal and response suggests that there might be a simpler way to model at least some important aspects of cell function. In the field of Artificial Intelligence, such simpler modelling methods for complex systems have been developed. In this paper, it is shown how the Artificial Intelligence description method for deliberative agents functioning on the basis of beliefs, desires and intentions as known in Artificial Intelligence, can be used successfully to describe essential aspects of cellular regulation. This is demonstrated for catabolite repression and substrate induction phenomena in the bacterium Escherichia coli. The method becomes highly efficient when the computation is automated in a Prolog implementation. By defining in a qualitative way the food supply of the bacterium, the make-up of its catabolic pathways is readily calculated for cases that are sufficiently complex to make the traditional human reasoning tedious and error prone.

Animals↗