Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

O erro médico na imprensa portuguesa: quando os pacientes fazem parte da notícia

Esta investigação aborda a qualidade da produção noticiosa sobre o erro médico, como um fator essencial na construção do conhecimento público sobre o tema, com o objetivo de compreender que características definem tal produção e até que ponto poderão ser explicadas pela periodicidade e orientação editorial dos jornais; que conceito de erro médico é veiculado pela produção noticiosa sobre o tema; e quais são os protagonistas no discurso jornalístico sobre o erro médico. Foram analisadas as edições de três jornais portugueses, de 2008 a 2011, resultando num corpus de 266 (4,2%) artigos, que foram classificados de acordo com as seguintes variáveis: as fontes de informação citadas (o seu estatuto e especialidade, no caso dos médicos); os temas que são tratados; as características de enquadramento da informação publicada (tom, género jornalístico; e a presença e número de fontes de informação). Pela análise de conteúdo quantitativa, apurou-se que esse tema está em crescimento, essencialmente com notícias de tom negativo e fontes de informação habitualmente identificadas. Não há evidência para afirmar que a periodicidade e a orientação editorial expliquem as variações dessas características, a não ser relativamente ao número de fontes citadas. Vigoram as notícias centradas nos resultados dos erros (mortes ou lesões), provocados por "erros de omissão" e por "erros de comissão", envolvendo uma diversidade de protagonistas: são, tal como acontece na informação sobre saúde em geral, fontes oficiais e especializadas do campo da saúde. Destacam-se os médicos e os juristas e é dado relevo aos pacientes.

Relatório de atividade profissional

Dissertação de mestrado em Ciências - Formação Contínua de Professores (área de especialização em Biologia e Geologia)

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Sistema de posicionamento baseado em redes de sensores sem fios

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

DNA evidence collecting in criminal investigation: Portuguese and Thai legal approaches

Doctoral Thesis in Juridical Sciences (Specialty in Public Legal Sciences)

Mother’s anxiety and depression and associated risk factors during early pregnancy: effects on fetal growth and activity at 20–22 weeks of gestation

To examine effects of mother's anxiety and depression and associated risk factors during early pregnancy on fetal growth and activity. Repeated measures of mother's anxiety (State-Anxiety Inventory (STAI-S)) and depression (Edinburgh Postnatal Depression Scale (EPDS)) and related socio demographics and substance consumption were obtained at the 1st and 2nd pregnancy trimesters, and fetus' (N = 147) biometric data and behavior was recorded during ultrasound examination at 20-22 weeks of gestation. Higher anxiety symptoms were associated to both lower fetal growth and higher fetal activity. While lower education, primiparity, adolescent motherhood, and tobacco consumption predicted lower fetal growth, coffee intake predicted lower fetal activity. Vulnerability of fetal development to mother's psychological symptoms as well as to other sociodemographic and substance consumption risk factors during early and mid pregnancy is suggested.

Antibacterial properties of multifunctional coatings Ag-ZrCN for biomedical devices: a novel approach

PhD in Sciences Specialty in Physics