899 resultados para Computacional Intelligence in Medecine
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Maddrell, John, 'The Scientist Who Came in from the Cold: Heinz Barwich's Flight from the GDR', Intelligence and National Security (2005) 20(4) pp.608-630 RAE2008
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The aim of this article is to present and discuss John Dewey’s and Walter Lippmann’s views on the problem of communication in a democratic society, particularly their views on the question of a role of communication in forming social processes. First part of the paper outlines the framework of this problem and its meaning to the question of possibility of democracy. Part two is concerned with anthropological and socio-political considerations: I discuss the Deweyan and the Lippmannian understanding of individual, society, intelligence and democracy. In part three I examine in detail the problem of communication, with special attention given to the questions of the role of communication in forming social processes, the foundations and conditions of communication, the debaters, and a subject matter of a debate as well as the questions of who and what forms this debate and whether we can form it altogether.
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In the analysis of relations among the elements of two sets it is usual to obtain different values depending on the point of view from which these relations are measured. The main goal of the paper is the modelization of these situations by means of a generalization of the L-fuzzy concept analysis called L-fuzzy bicontext. We study the L-fuzzy concepts of these L-fuzzy bicontexts obtaining some interesting results. Specifically, we will be able to classify the biconcepts of the L-fuzzy bicontext. Finally, a practical case is developed using this new tool.
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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas
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As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis
Towards a situation-awareness-driven design of operational business intelligence & analytics systems
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With the swamping and timeliness of data in the organizational context, the decision maker’s choice of an appropriate decision alternative in a given situation is defied. In particular, operational actors are facing the challenge to meet business-critical decisions in a short time and at high frequency. The construct of Situation Awareness (SA) has been established in cognitive psychology as a valid basis for understanding the behavior and decision making of human beings in complex and dynamic systems. SA gives decision makers the possibility to make informed, time-critical decisions and thereby improve the performance of the respective business process. This research paper leverages SA as starting point for a design science project for Operational Business Intelligence and Analytics systems and suggests a first version of design principles.
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A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1.
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It is estimated that 5.6% of the Tanzanian population ages 15-49 are infected with HIV, but only 30% of adults have ever had an HIV test. Couples' testing has proven to increase testing coverage and introduce HIV prevention, but barriers include access to testing services and unequal gender dynamics in relationships. Innovative approaches are needed to address barriers to couple's testing and increase uptake of HIV testing. Using qualitative data collection methods, a formative study was conducted to assess the acceptability of a home-based couples counseling and testing (HBCCT) approach. Eligible study participants included married men and women, HIV-infected individuals, health care and home-based care providers, voluntary counseling and testing counselors, and community leaders. A total of 91 individuals participated in focus group discussions (FGDs) and in-depth interviews conducted between September 2009 and January 2010 in rural settings in Northern Tanzania. An HBCCT intervention appears to be broadly acceptable among participants. Benefits of HBCCT were identified in terms of access, confidentiality, and strengthening the relationship. Fears of negative consequences from knowing one's HIV status, including stigma, blame, physical abuse, or divorce, remain a concern and a potential barrier to the successful provision of the intervention. Lessons for implementation highlighted the importance of appointments for home visits, building relationships of confidence and trust between counselors and clients, and assessing and responding to a couple's readiness to undergo HIV testing. HBCCT should addresses HIV stigma, emphasize confidentiality, and improve communication skills for disclosure and decision-making among couples.
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Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.
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OBJECTIVE: A study was undertaken to determine whether better cognitive functioning at midlife among more physically fit individuals reflects neuroprotection, by which fitness protects against age-related cognitive decline, or neuroselection, by which children with higher cognitive functioning select more active lifestyles. METHODS: Children in the Dunedin Longitudinal Study (N = 1,037) completed the Wechsler Intelligence Scales and the Trail Making, Rey Delayed Recall, and Grooved Pegboard tasks as children and again at midlife (age = 38 years). Adult cardiorespiratory fitness was assessed using a submaximal exercise test to estimate maximum oxygen consumption adjusted for body weight in milliliters/minute/kilogram. We tested whether more fit individuals had better cognitive functioning than their less fit counterparts (which could be consistent with neuroprotection), and whether better childhood cognitive functioning predisposed to better adult cardiorespiratory fitness (neuroselection). Finally, we examined possible mechanisms of neuroselection. RESULTS: Participants with better cardiorespiratory fitness had higher cognitive test scores at midlife. However, fitness-associated advantages in cognitive functioning were already present in childhood. After accounting for childhood baseline performance on the same cognitive tests, there was no association between cardiorespiratory fitness and midlife cognitive functioning. Socioeconomic and health advantages in childhood and healthier lifestyles during young adulthood explained most of the association between childhood cognitive functioning and adult cardiorespiratory fitness. INTERPRETATION: We found no evidence for a neuroprotective effect of cardiorespiratory fitness as of midlife. Instead, children with better cognitive functioning are selecting healthier lives. Fitness interventions may enhance cognitive functioning. However, observational and experimental studies testing neuroprotective effects of physical fitness should consider confounding by neuroselection.
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The pragmatics of 'vegetarian' and 'carnivorous' exhibits an asymmetry that we put in evidence by analyzing a newspaper report about vegetarian dog-owners imposing a vegetarian diet on their pets. More fundamental is the problem of partonomy versus containment, for which we attempt a naive but formal analysis applied to ingestion and the food chain, an issue we derive from the same text analyzed. Our formal tools belong in commonsense modelling, a domain of artificial intelligence related to extra-linguistic knowledge and pragmatics. We first provide an interpretation of events analyzed, and express it graphically in a semantic-network related representation, and propose an alternative that we express in terms of a modal logic, avoiding the full representational power of Hayes's "ontology for liquids".
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In this paper, a knowledge-based approach is proposed for the management of temporal information in process control. A common-sense theory of temporal constraints over processes/events, allowing relative temporal knowledge, is employed here as the temporal basis for the system. This theory supports duration reasoning and consistency checking, and accepts relative temporal knowledge which is in a form normally used by human operators. An architecture for process control is proposed which centres on an historical database consisting of events and processes, together with the qualitative temporal relationships between their occurrences. The dynamics of the system is expressed by means of three types of rule: database updating rules, process control rules, and data deletion rules. An example is provided in the form of a life scheduler, to illustrate the database and the rule sets. The example demonstrates the transitions of the database over time, and identifies the procedure in terms of a state transition model for the application. The dividing instant problem for logical inference is discussed with reference to this process control example, and it is shown how the temporal theory employed can be used to deal with the problem.
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Logic-based models are thriving within artificial intelligence. A great number of new logics have been defined, and their theory investigated. Epistemic logics introduce modal operators for knowledge or belief; deontic logics are about norms, and introduce operators of deontic necessity and possibility (i.e., obligation or prohibition). And then we have a much investigated class—temporal logics—to whose application to engineering this special issue is devoted. This kind of formalism deserves increased widespread recognition and application in engineering, a domain where other kinds of temporal models (e.g., Petri nets) are by now a fairly standard part of the modelling toolbox.