Interoperability on low power devices

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

NEGOSEIO: framework for the sustainability of model-oriented enterprise interoperability

Dissertation to obtain the degree of Doctor of Philosophy in Electrical and Computer Engineering(Industrial Information Systems)

Methodology for enterprise interoperability assessment

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Interoperability issues between learning object repositories and metadata harvesters

In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions.

Improving integrated care in chronic kidney failure patients with a standard-based interoperability framework.

This paper introduces the evaluation report after fostering a Standard-based Interoperability Framework (SIF) between the Virgen del Rocío University Hospital (VRUH) Haemodialysis (HD) Unit and 5 outsourced HD centres in order to improve integrated care by automatically sharing patients' Electronic Health Record (EHR) and lab test reports. A pre-post study was conducted during fourteen months. The number of lab test reports of both emergency and routine nature regarding to 379 outpatients was computed before and after the integration of the SIF. Before fostering SIF, 19.38 lab tests per patient were shared between VRUH and HD centres, 5.52 of them were of emergency nature while 13.85 were routine. After integrating SIF, 17.98 lab tests per patient were shared, 3.82 of them were of emergency nature while 14.16 were routine. The inclusion of a SIF in the HD Integrated Care Process has led to an average reduction of 1.39 (p=0.775) lab test requests per patient, including a reduction of 1.70 (p=0.084) in those of emergency nature, whereas an increase of 0.31 (p=0.062) was observed in routine lab tests. Fostering this strategy has led to the reduction in emergency lab test requests, which implies a potential improvement of the integrated care.

Interoperability and Technology for a Language Resources Factory

This document describes some of the technological aspects of a project devoted to the creation of a factory for language resources. The project’s objectives are explained, as well as the idea to create a distributed infrastructure of web services. This document focuses on two main topics of the factory: (1) the technological approaches chosen to develop the factory, i.e. software, protocols, servers, etc. (2) and Interoperability as the main challenge is to permit different NLP tools work together in the factory. This document explains why XCES and GrAF are chosen as the main formats used for the linguistic data exchange.

Guidelines for CERIF-XML Data Exchange with CSUC’s Catalan Research Portal (PRC) (Version 2.2)

The Catalan Research Portal (Portal de la Recerca de Catalunya or PRC) is an initiative carried out by the Consortium for University Services in Catalonia (CSUC) in coordination with nearly all universities in Catalonia. The Portal will provide an online CERIF-compliant collection of all research outputs produced by Catalan HEIs together with an appropriate contextual information describing the specific environment where the output was generated (such as researchers, research group, research project, etc). The initial emphasis of the Catalan Research Portal approach to research outputs will be made on publications, but other outputs such as patents and eventually research data will eventually be addressed as well. These guidelines provide information for PRC data providers to expose and exchange their research information metadata in CERIFXML compatible structure, thus allowing them not just to exchange validated CERIF XML data with the PRC platform, but to improve their general interoperability by being able to deliver CERIFcompatible outputs.

OpenAIRE Guidelines for Literature Repositories, Data Archives and CRIS managers

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Supporting Repository Interoperability through Guidelines

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

From Local Practice to Linked Open Data: Rethinking Metadata in Hydra

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Reusing repository data: migration of data between repositories

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014