3 research outputs found
Anotação automática e interativa de documentos PDF
Mestrado em Engenharia de Computadores e TelemáticaO aumento acelerado da literatura biomédica levou ao desenvolvimento de
vários esforços para extrair e armazenar, de forma estruturada, a informação
relativa aos conceitos e relações presentes nesses textos, oferecendo aos investigadores
e clínicos um acesso rápido e fácil à informação. No entanto,
este processo de "curadoria de conhecimento" é uma tarefa extremamente
exaustiva, sendo cada vez mais comum o uso de ferramentas de anotação
automática, fazendo uso de técnicas de mineração de texto. Apesar de já
existirem sistemas de anotação bastante completos e que apresentam um
alto desempenho, estes não são largamente usados pela comunidade biomédica,
principalmente por serem complexos e apresentarem limitações ao
nível de usabilidade. Por outro lado, o PDF tornou-se nos últimos anos num
dos formatos mais populares para publicar e partilhar documentos visto poder
ser apresentado exatamente da mesma maneira independentemente do
sistema ou plataforma em que é acedido. A maioria das ferramentas de anotação
foram principalmente desenhadas para extrair informação de texto livre,
contudo hoje em dia uma grande parte da literatura biomédica é publicada e
distribuída em PDF, e portanto a extração de informação de documentos PDF
deve ser um ponto de foco para a comunidade de mineração de texto biomédico.
O objetivo do trabalho descrito nesta dissertação foi a extensão da framework
Neji, permitindo o processamento de documentos em formato PDF, e a integração
dessas funcionalidades na plataforma Egas, permitindo que um utilizador
possa visualizar e anotar, simultaneamente, o artigo original no formato
PDF e o texto extraído deste.
Os sistemas desenvolvidos apresentam bons resultados de desempenho,
tanto em termos de velocidade de processamento como de representação da
informação, o que também contribui para uma melhor experiência de utilizador.
Além disso, apresentam várias vantagens para a comunidade de mineração
de texto e curadores, permitindo a anotação direta de artigos no formato
PDF e simplificando o uso e configuração destes sistemas de anotação por
parte de investigadores.The accelerated increase of the biomedical literature has led to various efforts
to extract and store, in a structured way, the information related with the
concepts and relations presented in those texts, providing to investigators and
researchers a fast and easy access to knowledge. However, this process of
“knowledge curation” is an extremely exhaustive task, being more and more
common demanding the application of automatic annotation tools, that make
use of text mining techniques. Even thought complete annotation systems already
exist and produce high performance results, they are not widely used by
the biomedical community, mainly because of their complexity and also due to
some limitations in usability. On the other hand, the PDF has become in the
last years one of the most popular formats for publishing and sharing documents
because of it can be displayed exactly in the same way independently
of the system or platform where it is accessed. The majority of annotation
tools were mainly designed to extract information from raw text, although a big
part of the biomedical literature is published and distributed in PDF, and thus
the information extraction from PDF documents should be a focus point for the
biomedical text mining community.
The objective of the work described in this document is the extension of Neji
framework, allowing the processing of documents in PDF format, and the integration
of these features in Egas platform, allowing a user to simultaneously
visualize the original article in PDF format and its extracted text.
The improved and developed systems present good performing results, both
in terms of processing speed and representation of the information, contributing
also for a better user experience. Besides that, they present several advantages
for the biomedical community, allowing the direct annotation of PDF
articles and simplifying the use and configuration of these annotation systems
by researchers
Single photon emission computed tomography, invasive coronary angiography and cardiac computed tomography angiography
Introduction: Diagnostic tests that use ionizing radiation play a central role in cardiology and their use has grown in recent years, leading to increasing concerns about their potential stochas-tic effects. The aims of this study were to compare the radiation dose of three diagnostic tests: single photon emission computed tomography (SPECT), invasive coronary angiography (ICA) and cardiac computed tomography (cardiac CT) and their evolution over time, and to assess the influence of body mass index on radiation dose. Methods: We assessed consecutive patients included in three prospective registries (SPECT, ICA and cardiac CT) over a period of two years. Radiation dose was converted to mSv and compared between the three registries. Differences over time were evaluated by comparing the first with the fourth semester. Results: A total of 6196 exams were evaluated: 35% SPECT, 53% ICA and 22% cardiac CT. Mean radiation dose was 10.7±1.2 mSv for SPECT, 8.1±6.4 mSv for ICA, and 5.4±3.8 mSv for cardiac CT (p<0.001 for all). With regard to the radiation dose over time, there was a very small reduction in SPECT (10.7 to 10.5 mSv, p=0.004), a significant increase (25%) in ICA (7.0 to 8.8mSv; p<0.001), and a significant reduction (29%) in cardiac CT (6.5 to 4.6 mSv, p<0.001). Obesity was associated with a significantly higher radiation dose in all three exams. Conclusions: Cardiac CT had a lower mean effective radiation dose than invasive coronary angiography, which in turn had a lower mean effective dose than SPECT. There was a significant increase in radiation doses in the ICA registry and a significant decrease in the cardiac CT registry over time.publishersversionpublishe