Repositorio Universidad Europea del Atlántico
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Machine Learning Models to Predict Readmission Risk of Patients with Schizophrenia in a Spanish Region
No full textCurrently, high hospital readmission rates have become a problem for mental health services, because it is directly associated with the quality of patient care. The development of predictive models with machine learning algorithms allows the assessment of readmission risk in hospitals. The main objective of this paper is to predict the readmission risk of patients with schizophrenia in a region of Spain, using machine learning algorithms. In this study, we used a dataset with 6089 electronic admission records corresponding to 3065 patients with schizophrenia disorders. Data were collected in the period 2005–2015 from acute units of 11 public hospitals in a Spain region. The Random Forest classifier obtained the best results in predicting the readmission risk, in the metrics accuracy = 0.817, recall = 0.887, F1-score = 0.877, and AUC = 0.879. This paper shows the algorithm with highest accuracy value and determines the factors associated with readmission risk of patients with schizophrenia in this population. It also shows that the development of predictive models with a machine learning approach can help improve patient care quality and develop preventive treatments
Rehabilitación Neuropsicológica e Intervención en Pacientes Afectados por Accidente Cerebrovascular (ACV). Una Revisión Bibliográfica.
No full textLos accidentes cerebrovasculares son frecuentes en la población: aproximadamente 800 mil personas al año los sufren. Estos pueden darse debido a varias causas, no obstante, consiste en que una parte neuro cerebral deja de recibir suficiente glucosa y oxígeno. Las secuelas van a depender del tiempo de esa privación, de su localización y de las funciones que tiene esa área y sus colindantes. La rehabilitación puede darse a lápiz y papel o usando tecnología, aunque lo ideal es integrar ambas formas de tratamiento. Los accidentes cerebrovasculares son muy limitantes y por ello la intervención temprana aumenta las probabilidades de una mejor recuperación
Trastorno por Atracón y Terapia Cognitivo Conductual
No full textSe ha llevado a cabo una revisión sobre los Trastornos de Conducta Alimentaria (TCA), específicamente sobre el Trastorno por Atracón (TA) y su intervención a través de la Terapia Cognitivo Conductual (TCC). El objetivo principal fue conocer la eficacia de la TCC frente a otras terapias, a la vez que se observaba la validez de la combinación entre la terapia citada y otras terapias o técnicas. También se centró en los beneficios de la terapia online. Metodología: Se realizó una revisión sistemática a través de la búsqueda de artículos publicados en las bases de datos “PubMed”, “Redalyc” y “APA Psycnet” a partir del año 2015 que estudiaban los efectos de la TCC combinando o comparando con otras terapias y en función de su formato online o presencial. Resultados: La terapia que ha presentado una alta tasa de mejora para el TA ha sido la TCC. Los resultados de la TCC en formato online han demostrado una mayor satisfacción por parte de los pacientes. Conclusiones: La TCC es la técnica más utilizada, eficaz y validada para llevar a cabo la intervención sobre el TA ya que reduce la frecuencia de los episodios de atracón, la posible sintomatología depresiva y la calidad de vida de los pacientes
Terapia Cognitivo-Conductual para el Trastorno de Pánico con o sin Agorafobia
No full textEl trastorno de pánico y agorafobia se consideran dos de los trastornos de ansiedad con mayor prevalencia y demanda para tratamiento. Pese a ser dos trastornos independientes, se pueden dar de forma conjunta. Para tratar este problema existen múltiples intervenciones. La terapia cognitivo-conductual (TCC) es una de las psicoterapias científicamente comprobadas que ha resultado efectiva a lo largo de la historia. Si bien es cierto que se ha demostrado esta efectividad, aún existe la necesidad de seguir investigando sobre las distintas técnicas. Es por ello que el objetivo de este proyecto se centra en realizar una revisión sistemática de aquellos estudios que investigan la terapia cognitivo-conductual para el trastorno de pánico con o sin agorafobia. De esta forma, los resultados de varios estudios son comparados y analizados minuciosamente, para así poder aclarar cuál es la mejor intervención para el tratamiento de este trastorno
Exploring the Chemistry of Ocimum Species under Specific Extractions and Chromatographic Methods: A Systematic Review
Get PDFOcimum is considered the largest genus in the Lamiacea family. The genus includes basil, a group of aromatic plants with a wide range of culinary uses that nowadays draws attention for its medicinal and pharmaceutical potential. This systematic review intends to explore the chemical composition of nonessential oils and their variation across different Ocimum species. Moreover, we aimed to identify the state of knowledge regarding the molecular space in this genus as well as the different methods of extraction/identification and geographical location. Seventy-nine eligible articles were selected for the final analysis, from which we extracted more than 300 molecules. We found that the countries with the highest number of studies into Ocimum species are India, Nigeria, Brazil, and Egypt. However, from all known species of Ocimum, only 12 were found to have an extensive chemical characterization, particularly Ocimum basilicum and Ocimum tenuiflorum. Our study focused especially on alcoholic, hydroalcoholic, and water extracts, in which the main techniques for compound identifications are GC-MS, LC-MS, and LC-UV. Across the compiled molecules, we found a wide variety of compounds, especially flavonoids, phenolic acids, and terpenoids, suggesting that this genus could be a very useful source of possible bioactive compounds. The information collected in this review also emphasizes the huge gap between the vast number of Ocimum species discovered and the number of studies in each of them that determined the chemical characterization
Food knowledge level among Tanzanian women of childbearing age: developing a score for the food knowledge questionnaire
Get PDFFood knowledge (FK) is one of the factors that contribute to malnutrition conditions in developing countries, together with food safety, food security and food access. FK is defined as ‘the competence to understand healthy nutrition concepts’; it impacts individuals’ life due to its relationship with food behaviour and eating habits. Therefore, acting on FK can represent a starting point for improving the health status of vulnerable populations. The authors present a total score of an FK questionnaire (FKQ) and its relation to the socio-demographic characteristics of a specific target population: Tanzanian women of childbearing age. The results of the manuscript complement evidence of construct validity of the FKQ by providing an algorithm to compute a total score as a measure of FK. The strength of this tool, and its score, lies in the fact that the questionnaire has been validated and is easy to administer
Plant-Based Milk Alternatives in Child Nutrition
Get PDFPlant-based milk alternatives can be distinguished in two main categories, differing in production processes and regulation: plant-based formulas and plant-based drinks. They are now a widely accepted class of products on the international market. The various plant-based milk alternatives differ in nutritional characteristics due to their origin and manufacturing; more importantly, whereas formulas from plant and cow origin can be used interchangeably, plant-based drinks are nutritionally different from cow’s milk and can be consumed by children subsequently to the use of formula. Several scientific organizations have expressed differing opinions on the use of these products in the diets of children. In the face of unanimous conclusions regarding the use of these products during the first year of life, in subsequent ages there were conflicting opinions regarding the timing, quantities, and type of product to be used. From the viewpoint of the child’s overall diet and health, it could be suggested that these foods be considered not as simple substitutes for cow’s milk, but as part of a varied diet, within individual advice of use. We suggest accepting the presence of these products in a baby’s diet (omnivores included), planning their use correctly in the context of a balanced diet, according to the specific product and the needs of the individual
Aroma characteristics of volatile compounds brought by variations in microbes in winemaking
No full textWine is a highly complex mixture of components with different chemical natures. These components largely define wine’s appearance, aroma, taste, and mouthfeel properties. Among them, aroma is among the most important indicators of wine’s sensory characteristics. The essence of winemaking ecosystem is the process of metabolic activities of diverse microbes including yeasts, lactic acid bacteria, and molds, which result in wines with complicated and diversified aromas. A better understanding of how these microbes affect wine’s aroma is a crucial step to producing premium quality wine. This study illustrates existing knowledge on the diversity and classification of wine aroma compounds and their microbial origin. Their contributions to wine characteristics are discussed, as well. Furthermore, we review the relationship between these microbes and wine aroma characteristics. This review broadens the discussion of wine aroma compounds to include more modern microbiological concepts, and it provides relevant background and suggests new directions for future research
Triple-Band Notched Ultra-Wideband Microstrip MIMO Antenna with Bluetooth Band
Get PDFIn this paper, a novel ultra-wideband UWB antenna element with triple-band notches is proposed. The proposed UWB radiator element operates from 2.03 GHz up to 15.04 GHz with triple rejected bands at the WiMAX band (3.28–3.8 GHz), WLAN band (5.05–5.9 GHz), and X-band (7.78–8.51 GHz). In addition, the radiator supports the Bluetooth band (2.4–2.483 GHz). Three different techniques were utilized to obtain the triple-band notches. An alpha-shaped coupled line with a stub-loaded resonator (SLR) band stop filter was inserted along the main feeding line before the radiator to obtain a WiMAX band notch characteristic. Two identical U-shaped slots were etched on the proposed UWB radiator to achieve WLAN band notch characteristics with a very high degree of selectivity. Two identical metallic frames of an octagon-shaped electromagnetic band gap structure (EBG) were placed along the main feeding line to achieve the notch characteristic with X-band satellite communication with high sharpness edges. A novel UWB multiple-input multiple-output (MIMO) radiator is proposed. The proposed UWB-MIMO radiator was fabricated on FR-4 substrate material and measured. The isolation between every two adjacent ports was below −20 dB over the FCC-UWB spectrum and the Bluetooth band for the four MIMO antennas. The envelope correlation coefficient (ECC) between the proposed antennas in MIMO does not exceed 0.05. The diversity gains (DG) for all the radiators are greater than 9.98 dB
An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation
Get PDFThe precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation