La educación en materia de prevención de salud representa un reto en el que México, debido a su diversidad social, cultural, geográfica, económica y política; tiene una deuda histórica. Si bien es cierto que esta situación debe enfrentarse desde varios flancos: educación, economía, condiciones de trabajo, disponibilidad de los servicios y profesionales de salud – entre muchos otros – es indudable que la tecnología debe jugar un papel importante en todos. La experiencia de otros países de establecer expedientes clínicos electrónicos universales permite comprobar que conocer el estado de salud de su población permite a los gobiernos tomar decisiones que impacten de manera positiva en la población. El objetivo de este estudio es evaluar la reacción de los actores sociales (pacientes y médicos) a un sistema personal de salud. Con este fin se desarrolló un Sistema Personal de Salud basado en Android y compatible con el estándar HL7 v3 y se comparó contra su equivalente en papel. Se agrega el contexto de la pandemia causada por el Covid-19 debido a que durante la fase de pruebas el país comenzó con la primera ola de contagios; lo que afectó de cierta forma el número de pruebas, pero a la vez demostró la importancia de estas herramientas en situaciones críticas. Los resultados permiten hacer inferencias importantes sobre las características que debe tener este tipo de herramientas para funcionar en el mercado mexicano.
Chatbots en redes sociales para el apoyo oportuno de estudiantes universitarios con síntomas de trastorno por déficit de la atención con hiperactividad [pág. 52-62] Revista Iberoamericana de Tecnología en Educación y Educación en Tecnología N°22 | ISSN 1850-9959 | Diciembre 2018 |
Suicide is considered a public health issue, and its early detection and treatment may contribute to its preven-tion. Automatic detection of suicidal ideation indicators within texts can be a useful tool to prevent it. In this work a corpus was compiled, which consists of poems written by twelve different poets, where six of them committed suicide. Two vector representations were experimented on, one with the total number of words and another with words related to negative emotional concepts. The vectors were clustered using two algorithms: K-Means and a K-Means with Particle Swarm Optimization hybrid. The efficiency of the vector representations and the used algorithms were compared, obtaining as result that, through the hybrid algorithm and the negative emotional concepts vocabulary, the groups of poets with suicidal ideation and without it could be distinguished with an accuracy of 0.98.
Abstract-This study presents a comprehensive solution to the collection management, which is based on the model for Cultural Objects (CCO). The developed system manages and spreads the collections that are safeguarded in museums and galleries more easily by using IT. In particular, we present our approach for a non-structured search and recovery of the objects based on the annotation of artwork images. In this methodology, we have introduced a faceted search used as a framework for multi-classification and for exploring/browsing complex information bases in a guided, yet unconstrained way, through a visual interface.
This work presents the development of an ontology for speech disorders in children, in order to become a tool to support therapists for diagnosis and possible treatment. Speech disorders are classified using a taxonomy obtained from a speech disorders corpus previously conformed. Based on this taxonomy, the ontology, which structures and formalizes concepts defined by the main topic authors, is developed. The ontology's main classes represent the taxonomic classification of speech disorders, their etiological origin, symptoms, and signs of each disorder, assessment, and intervention strategies; it also represents patients as it instances. A transcription module is also used to make different pronunciation tests and to obtain more detail of the characteristics presented by each patient to make the diagnosis. The development of the tool and the transcription module is based on Natural Language Processing (NLP) and Information Retrieval (IR) techniques. The importance of an early detection and diagnosis of a speech disorder-which can have a social, economic and educational impact-, lies in the fact that the prognosis of the treatment depends on the cause of the disorder and on an opportune treatment.
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