Luís Brito Elvas

ISCTE-Instituto Universitário de Lisboa | ISCTE · Department of Information Science and Technology

Background In response to the intricate language, specialized terminology outside everyday life, and the frequent presence of abbreviations and acronyms inherent in health care text data, domain adaptation techniques have emerged as crucial to transformer-based models. This refinement in the knowledge of the language models (LMs) allows for a bette...

The management and exchange of electronic health records (EHRs) remain critical challenges in healthcare, with fragmented systems, varied standards, and security concerns hindering seamless interoperability. These challenges compromise patient care and operational efficiency. This paper proposes a novel solution to address these issues by leveragin...

BACKGROUND In response to the intricate language, specialized terminology outside everyday life, and the frequent presence of abbreviations and acronyms inherent in health care text data, domain adaptation techniques have emerged as crucial to transformer-based models. This refinement in the knowledge of the language models (LMs) allows for a bette...

Urban environments are characterized by a complex soundscape that varies across different periods and geographical zones. This paper presents a novel approach for analyzing nocturnal urban noise patterns and identifying distinct zones using mobile phone data. Traditional noise-monitoring methods often require specialized equipment and are limited i...

Smart cities leverage technology and data to enhance the quality of urban life, including the management of points of interest (POIs) and visitor experiences. This paper explores the relationship between POIs and visitor behavior in smart cities, examining the impact of technology-driven solutions on understanding, analyzing, and optimizing visitor...

Although tourists generate a large amount of data (known as “big data”) when they visit cities, little is known about their spatial behavior. One of the most significant issues that has recently gained attention is mobile phone usage and user behavior tracking. A spatial and temporal data visualization approach was established with the purpose of f...

This paper presents an Internet of Things (IoT) system designed to collect and analyse information regarding the travel patterns and movements of individuals in densely populated locations, in the context of smart cities. People’s movements are retrieved from coarse-grained aggregated cellular network data without collecting sensitive information f...

Aortic stenosis (AS) is a critical cardiovascular condition that necessitates precise diagnosis for effective patient care. Despite a limited dataset comprising only 202 images, our study employs transfer learning to investigate the efficacy of five convolutional neural network (CNN) models, coupled with advanced computer vision techniques, in accu...

Cardiovascular diseases (CVDs) account for a significant portion of global mortality, emphasizing the need for effective strategies. This study focuses on myocardial infarction, pulmonary thromboembolism, and aortic stenosis, aiming to empower medical practitioners with tools for informed decision making and timely interventions. Drawing from data...

Data sharing and service reuse in the health sector pose significant privacy and security challenges. The European Commission recognizes health data as a unique and cost-effective resource for research, while the OECD emphasizes the need for privacy-protecting data governance systems. In this paper, we propose a novel approach to health data access...

BACKGROUND The digital age, with ICT, IoT, big data, has opened new opportunities for improving the delivery of healthcare services, in which data mining approach can help improve the hospital management process by providing a big picture identifying process efficiencies OBJECTIVE This is a multidisciplinary study where a data mining approach was...

Patient sensing and data analytics provide information that plays an important role in the patient care process. Patterns identified from data and Machine Learning (ML) algorithms can identify risk/abnormal patients’ data. Due to automatization this process can reduce workload of medical staff, as the algorithms alert for possible problems. We deve...

The diagnosis of many heart diseases involves the analysis of images from Computed Tomography (CT) or echocardiography, which is mainly done by a medical professional. By using Deep Learning (DL) algorithms, it is possible to create a data-driven tool capable of processing and classifying this type of image, to support physicians in their tasks, im...

Covid-19 has rapidly spread and affected millions of people worldwide. For that reason, the public healthcare system was overwhelmed and underprepared to deal with this pandemic. Covid-19 also interfered with the delivery of standard medical care, causing patients with chronic diseases to receive subpar care. As chronic heart failure becomes more c...

Conducting epidemiologic research usually requires a large amount of data to establish the natural history of a disease and achieve meaningful study design, and interpretations of findings. This is, however, a huge task because the healthcare domain is composed of a complex corpus and concepts that result in difficult ways to use and store data. Ad...

Data sharing and services reuse in the health sector is a significant problem due to privacy, and security issues. The European Commission has classified health data as a unique resource owing to the ability to do both prospective and retrospective research at a low cost. Similarly, the OECD encourages member nations to create and implement health...

Data sharing in the health sector represents a big problem due to privacy and security issues. Health data have tremendous value for organisations and criminals. The European Commission has classified health data as a unique resource owing to their ability to enable both retrospective and prospective research at a low cost. Similarly, the Organisat...

BACKGROUND Data sharing and services reuse in the health sector is a significant problem due to privacy, security issues. The European Commission has classified health data as a unique resource owing to the ability to do both prospective and retrospective research at a low cost. Similarly, the OECD encourages member nations to create and implement...

Due to the high level of unpredictability and the complexity of the information requirements, disaster management operations are information demanding. Emergency response planners should organize response operations efficiently and assign rescue teams to particular catastrophe areas with a high possibility of surviving. Making decisions becomes mor...

Traffic accidents in urban areas lead to reduced quality of life and added pressure in the cities’ infra-structures. In the context of smart city data is becoming available that allows a deeper analysis of the phenomenon. We propose a data fusion process from different information sources like road accidents, weather conditions, local authority rep...

Traffic accidents in urban areas lead to reduced quality of life and added pressure in the cities’ infra-structures. In the context of smart city data is becoming available that allows a deeper analysis of the phenomenon. We propose a data fusion process from different information sources like road accidents, weather conditions, local authority rep...

Health Remote Monitoring Systems (HRMS) offer the ability to address health-care human resource concerns. In developing nations, where pervasive mobile networks and device access are linking people like never before, HRMS are of special relevance. A fundamental aim of this research work is the realization of technological-based solution to triage a...

Background: The digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID...

Transportation contributes to more than 25% of the European Union’s (EU) Greenhouse Gas Emissions (GHG) emissions [...]

Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-scans that can be performed should be limited, restricting the patient’s monitoring. Computer Vision...

The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infras...

BACKGROUND The digital age, with ICT, IoT, and big data, has opened new opportunities for improving the delivery of healthcare services, with remote monitor systems playing a crucial role, reaching out to patients. The versatility and necessity of these systems has been demonstrated during the current COVID-19 pandemic. Health Remote Monitoring Sys...

Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to pe...