Browsing by Author "Carvalho, Victor"
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- 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.
- 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.
- QoLIS — Health business analitics platform based on quality of life related with healthPublication . Goncalves, Joaquim; Carvalho, Victor; Reis, Luís Paulo; Faria, Brígida Mónica; Rocha, ÁlvaroA capacidade de medir efetivamente a Qualidade de Vida Relacionada com a Saúde (QdVRS) é um aspecto-chave para descrever os impactos da doença, tratamento, ou outras lesões, além de normal e envelhecimento do paciente esperado. Durante as duas últimas décadas, a avaliação do estado de saúde do paciente foi sujeita a uma substancial mudança de paradigma, evoluindo de uma dependência predominante em medições bioquímicas e físicas para o foco em resultados de saúde com base na avaliação pessoal da doença. Existem vários instrumentos de medição para avaliar a Qualidade de Vida (QdV) em geral, e QdVRS em particular, mas a análise em tempo real de dados produzidos por estes instrumentos só é possível com a tecnologia associada a sistemas de apoio à decisão (SAD). O desenvolvimento destes tipos de sistemas de informação apresentam alguns problemas que devem ser resolvidos. O QoLIS (Quality of Life Information Systems)) é um HBA (Health Business Analitics) com base nma plataforma web que usa informações sobre a QdVRS, além de dados clínicos, para fornecer informações que permitem auxiliar o clínico na tomada de decisão e pode interagir com qualquer fonte de dados.
- Quality of life assessment: Estimation based on Rasch modelPublication . Goncalves, Joaquim; Reis, Luís Paulo; Faria, Brígida Mónica; Carvalho, Victor; Abreu, CarlaContinuous assessment of the quality of health-related life (HRQoL) of patients is an important aspect of health and gives rise to several readings. On one hand, the enormous amount of information that is generated allows the extraction of knowledge with great accuracy concerning the disease, the treatments and the impact it has on society, on the other hand, this continuous monitoring allows effective control and one timely intervention on the patient. The QoLIS platform has a set of characteristics advantageous over other, including the wide range of analyses that can be made from the results that it provides. However, the complexity of the calculus evolved on the models used, combined with the number of data processing, hamper its use in real time, hindering their use in the context of a medical appointment. Whereas the use of evaluation of quality of life (QoL) in the context of a appointment is an added value for everyone involved, it was necessary to develop and implement, on the QoLIS, a strategy for determining the value of QoL, by estimate, based on Rasch model (in order to provide the same set of responses) and whose response time allows its effective use.
- QVida+: Quality of life continuos estimation for clinical decision supportPublication . Reis, Luís Paulo; Faria, Brígida Monica; Gonçalves, Joaquim; Rocha, Álvaro; Carvalho, VictorAdvances in the last decades in the areas of medical science and patients treatment resulted in a decrease in the mortality rate but also an increase in the number of patients with chronic diseases. This increased life expectancy of patients with chronic diseases often involves great suffering and considerable adverse effects for the patients. Thus, in addition to prolonging life, it is essential to increase the quality of life (QoL) of patients. QoL is now considered an important aspect in clinical practice for patients with chronic illnesses, but the methods to assess, in an automatic or semi-automatic manner, QoL, and their use in clinical decision support are still underexplored and their applications are virtually inexistent. The QVida + solution is based on scientific and technological developments in the areas of quality of life and mobile devices, with the goal of creating a new paradigm for the evaluation and use of QoL in clinical practice. The solution devised is based on an adaptive information system (IS) able to use physical and behavioral data of the patient, gathered by sensors and mobile devices, in conjunction with machine learning techniques, allowing continuous assessment of QoL based on measurement tools that significantly reduce the questionnaires response time without affecting the patients daily life. Continuous assessment of QoL and its rapid use on a clinical decision support system will enable a better quality and more supported decision, patient-centered, by the physician, allowing for an increased quality of life of patients.
- Sleep quality of heavy vhicles’ professional drivers: an analysis based on self-perceived feedbackPublication . Faria, Brígida Mónica; Lopes, Tatiana; Oliveira, Alexandra; Pimenta, Rui; Gonçalves, Joaquim; Carvalho, Victor; Faria, Brigida Monica; Pimenta, Rui; Oliveira, AlexandraSleep is a crucial biological need for all individuals, being reparative on a physical and mental level. Driving heavy vehicles is a task that requires constant attention and vigilance, and sleep deprivation leads to behavioral and physiological changes that can develop sleep disorders which can put lives at risk The main objectives of this study are to describe and evaluate sleep quality, excessive daytime sleepiness, circadian preference, and risk of suffering from obstructive sleep apnea in a population of Portuguese professional drivers. To fulfill the objectives, 43 Portuguese professional drivers, between 23 and 63 years old, answered validated questionnaires: Epworth Sleepiness Scale, Morningness–Eveningness, Stop-Bang Questionnaire, and Pittsburgh Sleep Quality Index. Results indicated that older drivers tend to experience higher daytime sleepiness (11 ± 3.4; p = 0.002) and obstructive sleep apnea risk (4.5 ± 1.5; p = 0.03). Regarding sleep quality, the majority of drivers were classified with poor sleep quality (74.4%). It was possible to infer statistical differences between groups based on body mass index (p = 0.037), the type of route (p = 0.01), and physical activity (p = 0.005). Drivers have an indifferent circadian preference and small-course drivers have a worse sleep health perception. Therefore, it is essential to implement prevention programs, promoting the basic rules for better sleep quality as well as identifying sleep disorders to minimize possible road accidents.
- A survey on clinical decision support systems concerning quality of lifePublication . Reis, Luís Paulo; Faria, Brígida Mónica; Goncalves, Joaquim; Rocha, Álvaro; Carvalho, VictorAs a result of improved living conditions and the progress achieved in areas related to medicine, there is a decrease in the mortality rate but an increase in the number of patients with chronic diseases. Contrary to what happened until a few decades ago, patients with chronic diseases now have a high life expectancy. However, the patients increased life expectancy, often causes great pain and significant adverse effects. In addition to prolonging life, it is essential to increase the quality of life (QoL) of patients. The QoL is now considered an important aspect in clinical practice for patients with chronic illnesses, but the methods to assess QoL, in automatic or semi-automatic manners and their use in clinical decision support are still underexplored and their applications are virtually non-existent. This paper presents an overview of research related to health quality of Life, estimation of quality of life including its continuous estimation, modeling and behavioral recognition and representation of knowledge in this area and decision support systems for clinical decision making and quality of life related applications.