997 resultados para Diseases Classification


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Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems

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Since the first in vivo studies of cerebral function with radionuclides by Ingvar and Lassen, nuclear medicine (NM) brain applications have evolved dramatically, with marked improvements in both methods and tracers. Consequently it is now possible to assess not only cerebral blood flow and energy metabolism but also neurotransmission. Planar functional imaging was soon substituted by single-photon emission computed tomography (SPECT) and positron emission tomography (PET); it now has limited application in brain imaging, being reserved for the assessment of brain death.

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Semi quantification (SQ) in DaTScan® studies is broadly used in clinic daily basis, however there is a suspicious about its discriminative capability, and concordance with the diagnostic classification performed by the physician. Aim: Evaluate the discriminate capability of an adapted database and reference's values of healthy controls for the Dopamine Transporters (DAT) with 123I–FP-IT named DBRV adapted to Nuclear Medicine Department's protocol and population of Infanta Cristina's Hospital, and its concordance with the physician classification.

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The occurrence of different viruses in nasopharyngeal secretions from children less than 5 years old with acute respiratory infections (ARI) was investigated over a period of 4 years (1982-1985) in Rio de Janeiro. Of the viruses known to be associated with ARI, all but influenza C and parainfluenza types 1, 2 and 4 were found. Viruses were found more frequently in children attending emergency or pediatric wards than in outpatients. This was clearly related to the high incidence of respiratory syncytial virus (RSV) in the more severe cases of ARI. RSV positive specimens appeared mainly during the fall, over four consecutive years, showing a clear seasonal ocurrence of this virus. Emergency wards provide the best source of data for RSV surveillance, showing sharp increase in the number of positive cases coinciding with increased incidence of ARI cases. Adenovirus were the second most frequent viruses isolated and among these serotypes 1,2 and 7 were predominant. Influenza virus and parainfluenza virus type 3 were next in frequency. Influenza A virus were isolated with equal frequency in outpatient departments, emergency and pediatric wards. Influenza B was more frequent among outpatients. Parainfluenza type 3 caused outbreaks in the shanty town population annually during the late winter or spring and were isolated mainly from outpatients. Herpesvirus, enterovi-rus and rhinovirus were found less frequently. Other viruses than RSV and parainfluenza type 3 did not show a clear seasonal incidence.

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The clinical content of administrative databases includes, among others, patient demographic characteristics, and codes for diagnoses and procedures. The data in these databases is standardized, clearly defined, readily available, less expensive than collected by other means, and normally covers hospitalizations in entire geographic areas. Although with some limitations, this data is often used to evaluate the quality of healthcare. Under these circumstances, the quality of the data, for instance, errors, or it completeness, is of central importance and should never be ignored. Both the minimization of data quality problems and a deep knowledge about this data (e.g., how to select a patient group) are important for users in order to trust and to correctly interpret results. In this paper we present, discuss and give some recommendations for some problems found in these administrative databases. We also present a simple tool that can be used to screen the quality of data through the use of domain specific data quality indicators. These indicators can significantly contribute to better data, to give steps towards a continuous increase of data quality and, certainly, to better informed decision-making.

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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

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In the present paper we assess the performance of information-theoretic inspired risks functionals in multilayer perceptrons with reference to the two most popular ones, Mean Square Error and Cross-Entropy. The information-theoretic inspired risks, recently proposed, are: HS and HR2 are, respectively, the Shannon and quadratic Rényi entropies of the error; ZED is a risk reflecting the error density at zero errors; EXP is a generalized exponential risk, able to mimic a wide variety of risk functionals, including the information-thoeretic ones. The experiments were carried out with multilayer perceptrons on 35 public real-world datasets. All experiments were performed according to the same protocol. The statistical tests applied to the experimental results showed that the ubiquitous mean square error was the less interesting risk functional to be used by multilayer perceptrons. Namely, mean square error never achieved a significantly better classification performance than competing risks. Cross-entropy and EXP were the risks found by several tests to be significantly better than their competitors. Counts of significantly better and worse risks have also shown the usefulness of HS and HR2 for some datasets.