Browsing by Author "Reis, Luís Paulo"
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- An approach for assessing the distribution of reporting delay in portuguese AIDS dataPublication . Oliveira, Alexandra; Gaio, Ana Rita; da Costa, Joaquim Pinto; Reis, Luís PauloHIV/AIDS epidemic is an important public health problem. The burden of the epidemic is estimated from surveillance systems data. The collected information is incomplete, making the estimation a challenging task and the reported trends often biased. The most common incomplete-data problems, in this kind of data, are due to under-diagnosis and reporting delays, mainly in the most recent years. This is a classical problem for imputation methodologies. In this paper we study the distribution of AIDS reporting delays through a mix approach, combining longitudinal K-means with the generalized least squares method. While the former identifies homogeneous delay patterns, the latter estimated longitudinal regression curves. We found that a 2-cluster structure is appropriated to accommodate the heterogeneity in reporting delay on HIV/AIDS data and that the corresponding estimated delay curves are almost stationary over time.
- An approach to assess quality of life through biometric monitoring in cancer patientsPublication . Silva, Eliana; Aguiar, Joyce; Oliveira, Alexandra; Faria, Brígida Mónica; Reis, Luís Paulo; Carvalho, Victor; Gonçalves, Joaquim; Oliveira e Sá, JorgeCancer is a serious disease that causes significant disability and suffering, so naturally Health Related Quality of Life (HRQoL) is a major concern of patients, families and clinicians. This paper intends to relate biometric indices, in terms of HRV metrics, with self-perceived HRQoL from patients with lymphoma. Patients (N = 12) answered FACT questionnaire and used a smartband that collected biometrical data in real-time along the chemotherapy treatment. Our results revealed that Physical Well-Being, Total, Lymphoma subscale and FACT-Lym Trial Outcome domains seem to have a similar pattern that HRV metrics across the treatment cycles. In specific, the FACT domains and the HRV metrics have the lowest average levels on the first cycle and seem to increase along the following cycles (3rd and 6th cycles). This approach of continuous assessment of HRQoL will enable a better accuracy and more supported clinical decision.
- Análise sobre a escolha do curso e instituição dos estudantes da área de engenhariaPublication . Barros, David; Vasconcelos, Rosa; Costa, António Pedro; Reis, Luís Paulo; Faria, Brígida MónicaTodos os anos ingressam nas universidades portuguesas milhares de estudantes provenientes do concurso nacional de acesso ao ensino superior. Estes estudantes são alocados de acordo com a sua nota de candidatura e as suas preferências a um par estabelecimento-curso. Apesar das estatísticas oficiais fornecidas pelo Ministério da Ciência, Tecnologia e Ensino Superior (MCTES), nem sempre é possível retirar os indicadores relevantes para uma boa tomada de decisão por parte das Universidades sobre os cursos e vagas a oferecer. Este trabalho procura avaliar os fatores que irão influenciar os estudantes na sua escolha por um par estabelecimento-curso assim como compreender as diferentes variáveis que estão relacionadas com essa mesma atribuição de influência. Baseou-se num estudo empírico, observacional através da aplicação de questionário, com o respetivo estudo estatístico. Os resultados mostraram uma relação em maior número entre os fatores estudados e o género. Permitiram ainda concluir que os fatores prestígio da instituição, empregabilidade e desenvolvimento intelectual são os mais valorizados pelos estudantes.
- Analysis on the selection of course and institution of engineering studentsPublication . Barros, David; Vasconcelos, Rosa; Costa, António Pedro; Reis, Luís Paulo; Faria, Brígida MónicaEvery year thousands of students apply for access to higher education in Portuguese universities. These students are allocated according to their application, secondary school grades and their preference to distinct establishment-course pairs. Despite official statistics provided by the Ministry of Science, Technology and Higher Education (MCTES), it is not always possible to have the relevant indicators for universities make a good decision concerning courses and vacancies to offer. This study evaluates the factors that influence students in their choice of a pair establishment-course as well as understand the different variables that are related to the same attribution of influence. The study is observational and empirical using questionnaires, with the appropriate statistical analysis. The results showed a relation in greater number among the studied factors and gender. In conclusion the prestige of the institution, employment and intellectual development are the factors most valued by students.
- Applications of brain wave classification for controlling an intelligent wheelchairPublication . Avelar, Maria Carolina; Almeida, Patricia; Faria, Brígida Mónica; Reis, Luís PauloThe independence and autonomy of both elderly and disabled people have been a growing concern in today’s society. Therefore, wheelchairs have proven to be fundamental for the movement of these people with physical disabilities in the lower limbs, paralysis, or other type of restrictive diseases. Various adapted sensors can be employed in order to facilitate the wheelchair’s driving experience. This work develops the proof concept of a brain–computer interface (BCI), whose ultimate final goal will be to control an intelligent wheelchair. An event-related (de)synchronization neuro-mechanism will be used, since it corresponds to a synchronization, or desynchronization, in the mu and beta brain rhythms, during the execution, preparation, or imagination of motor actions. Two datasets were used for algorithm development: one from the IV competition of BCIs (A), acquired through twenty-two Ag/AgCl electrodes and encompassing motor imagery of the right and left hands, and feet; and the other (B) was obtained in the laboratory using an Emotiv EPOC headset, also with the same motor imaginary. Regarding feature extraction, several approaches were tested: namely, two versions of the signal’s power spectral density, followed by a filter bank version; the use of respective frequency coefficients; and, finally, two versions of the known method filter bank common spatial pattern (FBCSP). Concerning the results from the second version of FBCSP, dataset A presented an F1-score of 0.797 and a rather low false positive rate of 0.150. Moreover, the correspondent average kappa score reached the value of 0.693, which is in the same order of magnitude as 0.57, obtained by the competition. Regarding dataset B, the average value of the F1-score was 0.651, followed by a kappa score of 0.447, and a false positive rate of 0.471. However, it should be noted that some subjects from this dataset presented F1-scores of 0.747 and 0.911, suggesting that the movement imagery (MI) aptness of different users may influence their performance. In conclusion, it is possible to obtain promising results, using an architecture for a real-time application.
- Biometrics and quality of life of lymphoma patients: A longitudinal mixed‐model approachPublication . Oliveira, Alexandra; Silva, Eliana; Aguiar, Joyce; Faria, Brigida Monica; Reis, Luís Paulo; Cardoso, Henrique; Gonçalves, Joaquim; Sá, Jorge Oliveira e Carvalho; Victor, Marques HerlanderKnowledge Engineering has become essential in the fields of Medical and Health Care with emphasis for helping citizens to improve their health and quality of life. This includes individual methods and techniques in health‐related knowledge acquisition and representation and their application in the construction of intelligent systems capable of using the acquired information to improve the patients' health and/or quality of life. Haemato‐oncological diseases can provide significant disability and suffering, with severe symptoms and psychological distress. They can create difficulties in fulfilling professional, family and social roles, affecting an individual's quality of life. Health related quality of life (HRQoL) is a subjective concept but there is also an objective component related to physiological indicators. Some of these physiological indicators can be easily assessed by wearable technology such heart rate variability (HRV). This paper introduces an intelligent system to assess, in real‐time, potential HRV indices, that can predict HRQoL in lymphoma patients throughout chemotherapy treatment and to account the individuals' variability.
- Cerebral Palsy EEG Signals Classification: Facial Expressions and Thoughts for Driving an Intelligent WheelchairPublication . Faria, Brígida Mónica; Reis, Luís Paulo; Lau, NunoBrain Computer Interfaces (BCI) enables interaction between users and hardware systems, through the recognition of brainwave activity. However, the current BCI systems still have a very low accuracy on the recognition of facial expressions and thoughts. This makes it very difficult to use these devices to enable safe and robust commands of complex devices such as an Intelligent Wheelchair. This paper presents an approach to expand the use of a brain computer interface for driving an intelligent wheelchair by patients suffering from cerebral palsy. The approach was based on appropriate signal preprocessing based on Hjorth parameters, a forward approach for variable selection and several data mining algorithms for classification such as naive Bayes, neural networks and support vector machines. Experiments were performed using 30 individuals suffering from IV and V degrees of cerebral palsy on the Gross Motor Function (GMF) measure. The results achieved showed that the preprocessing and variable selection methods were effective enabling to improve the results of a commercial BCI product by 57%. With the developed system it was also possible for users to perform a circuit in a simulated environment using just facial expressions and thoughts.
- Classification model for cardiotocographiesPublication . Pereira, Ana; Salgado, Filipe; Reis, Luís Paulo; Faria, Brígida MónicaCardiotocography is a diagnostic exam performed from the 28th week of pregnancy that registers the fetus cardiac frequency and uterine contractions. From this exam results a cardiotocogram whose reading and observation of the patterns contained in it allow an evaluation of the baby's condition and the fetal vitality in the maternal womb. This work aims the creation of a classification model using Learning Algorithms/Data Mining using the tool Rapid Miner. The subject of study was a Data Set with information registered from a total of 2126 cardiotograms, with 23 attributes, properly classified by 3 specialized obstetricians as to the baby status, in three possible states, namely: N = Normal; S = Suspect; P = Pathologic. All models tested showed an overall accuracy greater than 80%. Therefore the usefulness of creating predictive models for the classification of this type of diagnosis is great.
- Data Mining and decision support systems for clinical application and quality of lifePublication . Ferreira, Mário; Reis, Luís Paulo; Faria, Brígida Mónica; Goncalves, Joaquim; Rocha, ÁlvaroThe development of new technologies, information systems, decision support systems and clinical parameters prediction algorithms using machine learning and data mining, opens a new outlook in many areas of health. In this context, the concept of Quality of Life (QOL) has relevance in health and the possibility of integrate this measure in developing systems Decision Support Clinic (SADC). Through individual expectation of physical well-being, psychological, mental, emotional and spiritual patient, clinical variables and quality of life assessment, we intend to make a study of data to establish correlations with clinical data and pharmaceutical data, socio-economic factors, among others, for obtaining knowledge in terms of behavioral patterns of chronically ill, reaching a number of reliable data and easily accessible, capable of enhancing the decision-making process on the part of specialist medical teams, seeking to improve treatments and consequently the quality of life related to health chronically ill. This paper studied and compared related studies that develop systems for decision support and prediction in the clinical area, with emphasis on studies in the area of quality of life.
- Data mining and electronic devices applied to quality of life related to health dataPublication . Goncalves, Joaquim; Faria, Brígida Mónica; Reis, Luís Paulo; Carvalho, Victor; Rocha, ÁlvaroThe development of new technologies, information systems, decision support systems and clinical parameters prediction algorithms using machine learning and data mining opens a new perspective in many area of health. In this context, relevance presents the concept of Quality of Life (QOL) in health and the possibility of developing Support Systems Clinical Decision (SADC) that use it. Through individual expectation of physical well-being, psychological, mental, emotional and spiritual patients, discussed variables and measures the quality of research area of life, we intend to make a study of data to establish correlations with laboratory, pharmaceutical data, socio-economic, among others, obtaining knowledge in terms of behavioral patterns of chronic patients, achieving a number of reliable data and easily accessible, capable of enhancing the decision-making process by the specialized medical teams, seeking to improve treatments and consequently the related quality of life with the Health chronically ill. This paper studied and compared related studies that develop systems for decision support and prediction in the clinical area, with emphasis on studies in the area of quality of life.