8 results match your criteria: "Hospital Zamora[Affiliation]"

Background: The development of new aetiological premises, such as the microbiota-gut-brain axis theory, evidences the influence of dietary and nutritional patterns on mental health, affecting the patient's quality of life in terms of physical and cardiovascular health. The aim was to determine the impact of a nutritional programme focused on increasing the intake of prebiotic and probiotic food on cardio-metabolic status in individuals with schizophrenia spectrum disorders in the contextual setting of the SARS-CoV-2 era.

Methods: A randomised clinical trial (two-arm, double-blind, balanced-block, six-month intervention) was conducted in a group of 50 individuals diagnosed with schizophrenia spectrum disorder during the SARS-CoV-2 confinement period.

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New computational methods have emerged through science and technology to support the diagnosis of mental health disorders. Predictive models developed from machine learning algorithms can identify disorders such as schizophrenia and support clinical decision making. This research aims to compare the performance of machine learning algorithms: Decision Tree, AdaBoost, Random Forest, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor in the prediction of hospitalized patients with schizophrenia.

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Objective: To provide a new perspective on integrated biomedical and psychosocial dementia research.

Background: Dementia is being recognized as a multifactorial syndrome, but there is little interaction between biomedical and psychosocial approaches. A way to improve scientific knowledge is to seek better understanding of the mechanisms underlying the interaction between biomedical and psychosocial paradigms.

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The QoE measurement has become a novel theme today. To achieve a quality service and minimize the negative impact that traffic on network can cause, it's very important to manage the devices that intervene in this service. Hence, the QoE evaluation allows obtaining benefits both customers and service providers.

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Internet of Things (IoT) has emerged as a new paradigm today, connecting a variety of physical and virtual elements integrated with electronic components, sensors, actuators and software to collect and exchange data. IoT is gaining increasing attention as a priority research topic in the Health sector in general and in specific areas such as Mental Health. The main objective of this paper is to show a review of the existing research works in the literature, referring to the main IoT services and applications in Mental Health diseases.

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Data Mining in medicine is an emerging field of great importance to provide a prognosis and deeper understanding of disease classification, specifically in Mental Health areas. The main objective of this paper is to present a review of the existing research works in the literature, referring to the techniques and algorithms of Data Mining in Mental Health, specifically in the most prevalent diseases such as: Dementia, Alzheimer, Schizophrenia and Depression. Academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct, Scopus and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present.

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