Representações e reinterpretações do caminhar: caso de estudo da Rua das Dunas em Castelo do Neiva, Viana do Castelo

Dissertação de mestrado integrado em Arquitectura (área de especialização em Cidade e Território)

As cores de Braga: levantamento cromático da rua do Souto e da rua D. Diogo de Sousa

Dissertação de mestrado integrado em Arquitectura (área de especialização em Cultura Arquitectónica)

As ruas da cidade e os tempos de crise: exercício de leitura

Publicado em "Tempos sociais e o mundo contemporâneo: as crises, as fases e as ruturas". ISBN 978-989-8600-23-3

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Clustering barotrauma patients in ICU–A data mining based approach using ventilator variables

Lecture Notes in Computer Science, 9273

Improving quality of medical service with mobile health software

An increasing number of m-Health applications are being developed benefiting health service delivery. In this paper, a new methodology based on the principle of calm computing applied to diagnostic and therapeutic procedure reporting is proposed. A mobile application was designed for the physicians of one of the Portuguese major hospitals, which takes advantage of a multi-agent interoperability platform, the Agency for the Integration, Diffusion and Archive (AIDA). This application allows the visualization of inpatients and outpatients medical reports in a quicker and safer manner, in addition to offer a remote access to information. This project shows the advantages in the use of mobile software in a medical environment but the first step is always to build or use an interoperability platform, flexible, adaptable and pervasive. The platform offers a comprehensive set of services that restricts the development of mobile software almost exclusively to the mobile user interface design. The technology was tested and assessed in a real context by intensivists.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Da transversalidade do eixo da Fonte Velha: uma proposta de requalificação em duas ações

Dissertação de mestrado integrado em Arquitectura

Processos de melhoria social: a requalificação do Bairro Social de Santa Tecla

Dissertação de mestrado integrado em Arquitectura

Processo SAAL: o contributo para a concepção arquitectónica da habitação social

Dissertação de mestrado integrado em Arquitectura

Possibilidades de reabilitação urbana em bairros sociais: estudo de caso: Bairro Social de Santa Tecla, Braga

Dissertação de mestrado integrado em Engenharia Civil

Using mouse dynamics to assess stress during online exams

"Lecture notes in computer science series", ISSN 0302-9743, vol. 9121

O turismo religioso na Semana Santa em Braga

Relatório de estágio de mestrado em Sociologia (área de Especialização em Organizações e Trabalho)

Videovigilância: privacidade e segurança: análise especial da situação do trabalhador

Dissertação de mestrado em Direitos Humanos