Intelligent technologies for health self-management

El objetivo del proyecto “Tecnologías inteligentes para la autogestión de la salud” es desarrollar una plataforma inteligente para la autogestión de la salud de enfermedades crónicas como el asma y la obesidad. El sistema pone a disposición de los pacientes un servicio y control médico de primera mano, utilizando información que proporcione el mismo paciente y otra información textual proveniente de medios sociales como Twitter y otras fuentes oficiales que puedan ayudar a informar y apoyar a los usuarios según la enfermedad que padezcan. Esta información textual se procesará mediante tecnologías de análisis de sentimientos y clasificación para determinar si es una información relevante para cada paciente. Este proyecto está siendo desarrollado el grupo de investigación de informática médica de la Universidad de Guayaquil en colaboración con el grupo de investigación TECNOMOD de la Universidad de Murcia dentro del programa de ayudas propio de la Universidad de Guayaquil denominado FCI.The objective of "Intelligent technologies for health self-management" project is the development of an intelligent platform for the self-management of chronic diseases such as asthma and obesity. With this platform, patients can enhance their health management though information provided by themselves and by extracting textual information from Twitter and official sources to inform and help them in the treatment of the disease they suffer. This textual information will be processed through sentiment analysis and classification technologies to determine which information is relevant for each patient. This project is being developed by the medical informatics research group of the University of Guayaquil in collaboration with the TECNOMOD research group of the University of Murcia within the program of grants owned by the University of Guayaquil called FCI.Este trabajo ha sido financiado por la Universidad de Guayaquil dentro del proyecto “Tecnologías inteligentes para la autogestión de la salud” dentro de las ayudas FCI

Prevention of infectious diseases based on intelligent analysis in social networks and citizen participation

Este proyecto consiste en el desarrollo una plataforma inteligente de monitorización de enfermedades infecciosas a partir de la monitorización de redes sociales, fuentes de datos oficiales y la participación ciudadana. Esta información estará disponible para las autoridades sanitarias y gubernamentales a través de un panel de mandos personalizable para que puedan detectar zonas calientes en las que exista algún tipo de brote o focos de infección. También estará disponible un sistema de alertas para avisar a los ciudadanos cuándo se ha detectado cierto nivel de alarma en radio cercano a donde se encuentran. Este proyecto está siendo desarrollado por la empresa de Ecuador VIAMÁTICA, algunos docentes de la Universidad de Guayaquil, la empresa española DANTIA y las Universidades de Murcia y Carlos III de Madrid. La parte española del proyecto está financiada mediante una convocatoria de proyectos unilaterales del CDTI.This project consists in the development of an intelligent platform for the monitoring of infectious diseases based on: text written in natural language on social networks, official data sources and citizen participation. This information will be available to the health and governmental authorities through a customizable control panel so they can detect hot areas in which there is some type of outbreak. An alert system will also be available to notify citizens when a certain level of alarm is detected in a nearby radius of where they are. This project is being developed by VIAMÁTICA (Ecuador), the University of Guayaquil (Ecuador), DANTIA (Spain) and the Universities of Murcia and Carlos III of Madrid (Spain). The Spanish part of the project is financed through the unilateral CDTI projects call.Este trabajo está siendo financiado por el CDTI dentro del proyecto con referencia IDI-20180989 dentro de la convocatoria de proyectos unilaterales

Comparing Deep-Learning Architectures and Traditional Machine-Learning Approaches for Satire Identification in Spanish Tweets

Automatic satire identification can help to identify texts in which the intended meaning differs from the literal meaning, improving tasks such as sentiment analysis, fake news detection or natural-language user interfaces. Typically, satire identification is performed by training a supervised classifier for finding linguistic clues that can determine whether a text is satirical or not. For this, the state-of-the-art relies on neural networks fed with word embeddings that are capable of learning interesting characteristics regarding the way humans communicate. However, as far as our knowledge goes, there are no comprehensive studies that evaluate these techniques in Spanish in the satire identification domain. Consequently, in this work we evaluate several deep-learning architectures with Spanish pre-trained word-embeddings and compare the results with strong baselines based on term-counting features. This evaluation is performed with two datasets that contain satirical and non-satirical tweets written in two Spanish variants: European Spanish and Mexican Spanish. Our experimentation revealed that term-counting features achieved similar results to deep-learning approaches based on word-embeddings, both outperforming previous results based on linguistic features. Our results suggest that term-counting features and traditional machine learning models provide competitive results regarding automatic satire identification, slightly outperforming state-of-the-art models