Computer-aided diagnosis in Brain Computer Tomography screening

Currently, interpretation of medical images is almost exclusively made by specialized physicians. Although, the next decades will most certainly be of change and computer-aided diagnosis systems will play an important role in the reading process. Assisted interpretation of medical images has become one of the major research subjects in medical imaging and diagnostic radiology. From a methodological point of view, the main attraction for the resolution of this kind of problem arises from the combination of the image reading made by the radiologists, with the results obtained from using Artificial Intelligence (AI) based applications that will contribute to the reduction and eventually the elimination of perception errors. This article describes how machine learning algorithms can help distinguish normal readings in Brain Computer Tomography (CT) from all its variations. The goal is to have a system that is able to identify abnormal appearing structures making the reading by the radiologist unnecessary for a large proportion of the brain CT scans.(undefined

A new architecture for intelligent clinical decision support for intensive medicine

Real-time and intelligent decision support systems are of most importance to supply intensive care professionals with important information in useful time. The work presented hereby shows an architectural overview of the communication system with bedside devices such as vital sign monitors. Intelligent Decision Support System for Intensive Medicine (ICDS4IM) goal is to ensure information quality and availability to Intensive Medicine professionals to take supported decisions in a mutable environment where complex and unpredictable events are a common state. Therefore, this work focus on Health Information Systems, Interoperability and Information Diffusion and Archive. Moreover, communication standards and the usage of a new technology such as containerization are discussed. (C) 2020 The Authors. Published by Elsevier B.V.The work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the Projects Scope: UID/CEC/00319/2020 and DSAIPA/DS/0084/2018

Predictive analytics to support diabetic patient detection

The strong growth in the number of diabetics in recent years has become a major health concern. The dependence on sugar consumption has caused a rapid growth in the level of diagnoses and in the number of deaths associated. In this context, the project developed allowed a study on how Diabetes can be detected in a timely manner, through the existence of pre-indicators of the disease, defining factors that may determine its onset. For this study, data are collected from Hospital de Santa Luzia (ULSAM), considering aspects such as patient profile, prescribed drugs and previous diagnoses. The results prove that machine learning models using profile data with medical drugs produced the best results, optimizing the predictive ability of Diabetes.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/202

Predictive data mining in nutrition therapy

The assessment and measurement of health status in communities throughput the world is a massive information technology challenge. Data mining, plays a vital role in health care industry since it really has the potential to generate a knowledge-rich environment that reduces medical errors, decreases costs by increasing efficiency, improves the quality of clinical decisions and significantly enhances patient's outcomes and quality of life. This study falls within the context of nutrition evaluation and its main goal is to apply classification algorithms in order to predict if a patient needs to be followed by a nutrition specialist. One of the tools resorted in this study was the Waikato Environment for Knowledge Analysis (Weka in advance) Workbench since it allows to quickly try out and compare different machine learning solutions. The tasks involved in the development of this project included data preparation, data preprocessing, data transformation and cleaning, application of several classifiers and its respective evaluation through performance measures that include the confusion matrix, accuracy, error rate, and others. The accomplished results showed to be quite optimistic presenting promising values of performance measures. specifically an accuracy around 91 %.This work has been supported by Compete: POCI-01-0145-FEDER-007043 and FCT within the Project Scope UID/CEC/00319/2013

Improving the effectiveness of heart disease diagnosis with Machine Learning

First Online: 13 October 2022Despite technological and clinical improvements, heart disease remains one of the leading causes of death worldwide. A significant shift in the paradigm would be for medical teams to be able to accurately identify, at an early stage, whether a patient is at risk of developing or having heart disease, using data from their health records paired with Data Mining tools. As a result, the goal of this research is to determine whether a patient has a cardiac condition by using Data Mining methods and patient information to aid in the construction of a Clinical Decision Support System. With this purpose, we use the CRISP-DM technique to try to forecast the occurrence of cardiac disorders. The greatest results were obtained utilizing the Random Forest technique and the Percentage Split sampling method with a 66% training rate. Other approaches, such as Naïve Bayes, J48, and Sequential Minimal Optimization, also produced excellent results.This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Optimization of municipal solid waste collection routes based on the containers' fill status data

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Os laços da idade: evelhecimento e ocupação do tempo em Celorico de Basto

Dissertação de mestrado em Sociologia (área de especialização em Desenvolvimento e Políticas Sociais)O presente estudo foi realizado com o objetivo de conhecer melhor os hábitos de vida diários dos idosos de forma a compreender quais os efeitos destes mesmos hábitos no seu envelhecimento. Foi realizado numa amostra de idosos heterogénea quanto à classe social, à escolaridade, às profissões exercidas e rendimentos, do concelho de Celorico de Basto. O guião da entrevista aparece dividido em sete partes. E são elas: caracterização dos entrevistados (idade, sexo, estado civil, composição do agregado e local de residência); perfil de preferência de ocupação do tempo; perfil socioeconómico e socioprofissional; condições de saúde; redes sociais e familiares; equipamentos de apoio a idosos e serviços de ocupação de tempos livres; e por último as auto perceções em relação à velhice. Para isso contou-se com uma amostra de 10 idosos, com idades compreendidas entre 65 e os 80 anos de idade. O estudo seguiu uma abordagem metodológica qualitativa com recurso à entrevista como técnica de recolha de dados, evidenciando-se os perfis de preferência de ocupação do tempo, adotados pelos idosos, bem como, a forma como os idosos encaram a sua velhice. A análise dos dados permitiu concluir que os idosos vivenciam o envelhecimento de diferentes formas, no entanto todos acham importante o convívio e o contacto com a família e amigos como forma de combater a solidão e o isolamento. Constatou-se que existem diferentes formas de ocupação do tempo, que vão desde a realização de atividades domésticas e agrícolas até á utilização da internet e das redes sociais. Apesar de os entrevistados admitirem alguns problemas de saúde, todos dizem ser autónomos na realização das suas atividades diárias. Verificamos, que manterem-se independentes é uma das suas principais preocupações. Apresentam uma situação económica favorável apesar de alguns terem outras formas de sustento para além da reforma. De um modo geral, os idosos encaram a sua velhice com otimismo e encontram-se conformados com a sua situação de idosos como sendo o ciclo natural da vida. A maneira como lidam com a velhice depende da história de vida do indivíduo.This study was carried out to have a wider knowledge of the daily habits of the elderly and therefore understand its effects on their aging process. It was done in the municipality of Celorico de Basto, using an heterogeneous sample of elderly in terms of social background, education level, jobs and income. The interview is divided into 7 parts: features of the persons (age, gender, civil status, family and place where they live); profile in terms of occupation of time; social, economical and professional profile; conditions of health; family and social bonds; equipments for elderly support and free time occupation services; and their own perception of old age. The sample contains 10 elderly between 65 and 80 years old. The study pursued a qualitative approach, using the interview as a technique for data collection and it highlights the preferences for the occupation of time chosen by the elderly, as well as how they look at their old age. The data analysis showed that the elderly react to aging in different ways, but all of them see as very important the social contacts with the family and friends. It was observed that there are different ways of occupation of time: from domestic and agricultural activities to internet and social networks. Although some of them admited some health problems, they all claim to be autonomous in their daily routines. We saw that keeping independent is one of their major concerns. They have a good economic situation and some of them have other income appart from their pension. In general terms, the elderly see their old age with optimism and are resigned to their condition of elderly as a natural cycle of life. The way they deal with old age depends on their own life history

Steps towards intelligent diabetic foot ulcer follow-up based on deep learning

Diabetes is a chronic disease that affects the effective production of insulin in an individual. This incapacity leads to great damage to the cardiovascular system as well as the nervous system. Unfortunately this is a very present disease in today’s population. Indeed, global diabetes prevalence is estimated to be between 9,5% and 10,5%. Diabetic patients have a need for constant monitoring and evaluation by the healthcare professional whenever diabetic foot wounds show symptoms of infection and ulceration. The high number of patients with this diagnosis makes follow-up a problem for health professionals as well as for the patient. Lack of communication and access to health care are major contributing factors to lower extremity amputations, high mortality and morbidity interventions. In order to solve this gap, the present work presents an architecture for the development of a collaborative and decision support tool, between not only health professionals but also patients, capable of rapidly and automatically identifying, assessing and treating ulcer and symptoms of the pathology. This automation will be implemented through classification models with Deep Learning.FCT - Fundação para a Ciência e a Tecnologia(NORTE-01-0145-FEDER-000086

Steps towards interoperability in healthcare environment

Tese doutoramento - Programa Doutoral em Engenharia Biomédica, Informática MédicaHealthcare units have complex Information Systems (IS) made up from heterogeneous data sources, which speak di erent languages and with di erent objectives. Nevertheless, all these sources have indeed important information that can contribute in an active way to provide a healthcare system of excellence. The evolution that has been noticed in Health IS has promoted the development of new methodologies and tools that are intended to solve this complicated problem. In this manner, one of the main paradigms that arises is the interoperability among systems and its capability to allow a general and simpli ed access to relevant information. Another aspect that should be kept in mind, given the constrains of the global economic situation, is the reduction in the investment in national healthcare systems. This thesis is based on a set of studies performed at the Centro Hospitalar do T^amega e Sousa (CHTS) in which the main goals are promoting an improvement in the relation patient-hospital, having in consideration the reduction of implementation costs, but preserving the quality of information. The last one should be accessible everywhere and at anytime to help with clinical decision and, in the future, be available for clinical studies through data computationally interpretable. To do so, an Electronic Semantic Health Record was formalized and implemented, with the help of the clinical sta , which collects all the information considered important and relevant. This Health Record was delivered through a platform for the distribution and archive of clinical information, named Agency for the Integration, Di usion and Archive (AIDA), which is supported by intelligent agents that treat data in an ex-haustive and structured way. To test the proposed model and system and in order to strengthen the relation between the patient and the hospital, an appointment alert system based on SMS and electronic mail was developed, which allowed the reduction of non-programmed misses and that provided a decrease of costs by better re-distributed appointment schedules, and allocate human resources and physical spaces in a more e ective manner. Finally, to reduce stopping periods of systems and to promote the user's con dence on Information Systems, an open-source tool was developed that enables the scheduling of preventive actions according to a mathematical model. These tools allowed for a continuous improvement of systems and are currently well accepted by clinicians and Information Technologies (IT) specialists inside the healthcare unit, proving in real clinical situation the e ectiveness and usability of the model.As unidades de saúde possuem Sistemas de Informação (SI) complexos, compostos por fontes de dados heterogéneas com objectivos distintos. Por em, toda a informação e importante e pode contribuir de forma ativa para a prestação de cuidados de saúde de excelência. Com a evolução dos SI na Saúde novas metodologias têm sido desenvolvidas com o intuito de solucionar este problema complicado. Nesta perspectiva, um dos principais paradigmas que se coloca e a interoperabilidade entre sistemas e a sua capacidade para permitir um acesso simples a informação relevante. Outro factor relevante relaciona-se com os constrangimentos financeiros que toda a economia global atravessa e que se reflete numa diminuição no investimento nos servi cos nacionais de saúde. Esta tese tem como base um conjunto de estudos realizados no Centro Hospitalar do Tâmega e Sousa cujos principais objetivos se prendem com um esforço orientado para a melhoria da relação paciente-hospital, tendo em conta a redução de custos de implementação, mas garantindo sobretudo a qualidade de informação. Esta dever a estar disponível em qualquer lugar e a qualquer altura para o auxílio a decisão clinica e, em última instancia, disponível para estudos cl nicos através de dados interpretáveis computacionalmente. Para tal, recorreu-se a ajuda de pessoal clinico para a implementação de um Processo Clínico Eletrónico Semântico que recolhe toda a informação considerada relevante. Este Processo Clínico foi potenciado através de uma plataforma para a distribuição e arquivo de informação clinica, denominada de Agencia para a Interoperação, Difusão e Arquivo (AIDA), baseada em agentes inteligentes que tratam os dados de forma estruturada. Para testar o modelo e de forma a fortalecer a relação paciente-hospital foi desenvolvido um sistema de alertas para consulta via mensagens escritas e e-mail, que diminuiu o numero de faltas não programadas, proporcionando uma redução de custos através de uma redistribuição dos tempos de consulta alocando recursos humanos e físicos de forma mais eficaz. Por fim, com vista a redução dos tempos de paragem de sistemas, e potenciar a confiança dos utilizadores nos mesmos, foi desenvolvida uma ferramenta baseada em tecnologia open-source que permite o agendamento de intervenções preventivas de acordo com um modelo matemático. Esta ferramenta proporcionou uma melhoria contínua dos sistemas e está globalmente aceite por cl nicos e especialistas de Tecnologias de Informação (TI), provando em situações clínicas reais a usabilidade e eficácia do modelo