Conocimiento en la Mejora de los Procesos de Negocio

Concientes del papel fundamental del conocimiento para el éxito de las organizaciones, este artículo presenta un revisión de la literatura con el fin de conocer cual es el aporte del conocimiento dentro de la mejora de procesos de negocio. Se trae a discusión dos caminos a seguir, la automatización y la continua incorporación del conocimiento en los procesos. La tecnológica debe ocupar un lugar en las empresas solo después que la mejora de procesos ha sido implementada. Por otro lado, la incorporación continua de conocimiento en los procesos permite formar un circulo repetitivo de mejora de procesos.Sociedad Argentina de Informática e Investigación Operativ

Modelamiento de tópicos utilizando mensajes de Twitter relacionados al cáncer cervical

Cervical cancer is a worldwide health problem that generates a large amount of information that circulates through social networks. Topic modeling allows to automatically identify the topics covered in a set of documents. In the present work, topic modeling has been applied to identify topics from a set of tweets that deal with cervical cancer. The LDA algorithm and the coherence metric were applied for the evaluation. Seven topics related to the effect of HPV vaccines were identified, the relationship between HPV and other diseases, forms of prevention such as vaccines and Pap tests, programs that provide medical services for the prevention and elimination of this disease, stories of women who have suffered from cervical cancer and studies targeting Latina women.El cáncer cervical es un problema de salud a nivel mundial que genera una gran cantidad de información que circula por las redes sociales. El modelado de tópicos permite automáticamente identificar los tópicos que tratan en un conjunto de documentos. En el presente trabajo se ha aplicado modelamiento de tópicos para identificar tópicos de un conjunto de tweets que tratan sobre al cáncer cervical. Se aplicó el algoritmo LDA y la métrica de la coherencia para la evaluación. Se identificaron 7 tópicos relacionados al efecto de las vacunas contra el VPH, la relación que existe entre el VPH y otras enfermedades, formas de prevención como vacunas y test de Papanicolaou, programas que prestan servicios médicos para la prevención y eliminación de esta enfermedad, historias de mujeres que han padecido de cáncer cervical y estudios dirigidos a mujeres latinas

Computer-based identification of relationships between medical concepts and cluster analysis in clinical notes

Clinical notes contain information about medical concepts or entities (such as diseases, treatments and drugs) that provide a comprehensive and overall impression of the patient’s health. The automatic extraction of these entities is relevant for health experts and researchers as they identify associations between the latter. However, automatically extracting information from clinical notes is challenging, due to their narrative format. This research describes a process to automatically extract and aggregate medical entities from clinical notes, as well as the process to identify clusters of patients and disease-treatment relationships. The i2b2 2008 Obesity dataset was used, and consists of 1237 discharge summaries of overweight and diabetic patients. Therefore, this thesis is focused on obesity diseases. For the automatic extraction of medical entities, MetaMap and cTAKES were used, and the automatic extraction capacity of both tools compared. Also, UMLS enabled the aggregation of the extracted entities. Two approaches were applied for cluster analysis. Firstly, a sparse K-means algorithm was used over a patient-disease matrix with 14 comorbidities related to obesity. Secondly, to visualize and analyze other diseases present in the clinical notes, 86 diseases were used to identify clusters of patients with a network-based approach. Furthermore, bipartite graphs were used to explore disease-treatment relationships among some of the clusters obtained. The result of the experiments we conducted show cTAKES slightly outperforming MetaMap, but this situation can change, considering other configuration options in the respective tools, including an abbreviation list. Moreover, concept aggregation (with similar and different semantic types) was shown to be a good strategy for improving medical entity extraction. The sparse K-means enabled identification of three types of clusters (high, medium and low), based on the number of comorbidities and the percentage of patients suffering from them. These results show that diabetes, hypercholesterolemia, atherosclerotic cardiovascular diseases, congestive heart failure, obstructive sleep apnea, and depression were the most prevalent diseases. With the network approach, it was possible to visualize and analyze patient information. In it, three sub-graphs or clusters were identified: obese patients with metabolic problems, obese patients with infection problems, and obese patients with a mechanical problem. Bipartite graphs for a disease-treatment relationship showed treatments for different types of diseases, which means that obese patients are suffering from multiple diseases. This work shows that clinical notes are a rich source of information, and they can be used to explore, visualize, and analyze patient’s information by applying different approaches. More work is needed to explore the relationship between the different medical entities from clinical notes and from different disease datasets. Also, considering that some medical documents express events in time, this characteristic should be considered in future works to form a personalized portrait of clusters, diseases and patients

Centro de Interpretación e Investigación para las ocupaciones de Maranga en el distrito de San Miguel

La ardua labor de investigación acerca del Complejo Arqueológico Maranga, nace en 1992 con el lema algo más que un zoológico (Carrión y Narváez, 2014) por parte del Parque de las Leyendas, cuando se destinó la programación de un día a la semana para tomar acciones respecto a los monumentos arqueológicos, empezando a discutirse temas sobre conservación, restauración y la defensa de los mismos. Sin embargo, ya en la década de 1960, los especialistas José Casafranca y Lorenzo Roselló, habiendo estudiado dos de los monumentos, facilitaron el primer paso para continuar la investigación en la zona. Las primeras personas en involucrarse en este tema, fueron los arqueólogos del sitio: Lucénida Carrión, Denise Pozzi-Escot, Juan Paredes, María Isabel Fuentealba, Donal Gutiérrez e Inés del Águila, asesora del Parque de las Leyendas. Para ello analizaron cuál era la situación de estos monumentos y así tomar acciones de emergencia, pues era evidente que con el crecimiento urbano, las personas habían invadido terrenos amenazando el sitio arqueológico. Posterior al desalojo legal de las personas, se empezaron las acciones de conservación y restauración de cada monumento, comenzando por la limpieza y recolección de datos de lo que existía, elaborando planos catastrales y mapas de todo el Complejo Arqueológico como conjunto, asimismo se registraron todos los hallazgos realizando los inventarios respectivos.Tesi

Personality profiles of cultures: aggregate personality traits

Personality profiles of cultures can be operationalized as the mean trait levels of culture members. College students from 51 cultures rated an individual from their country whom they knew well (N = 12, 156). Aggregate scores on Revised NEO Personality Inventory scales generalized across age and gender groups, approximated the individual-level Five-Factor Model, and correlated with aggregate self-report personality scores and other culture-level variables. Results were not attributable to national differences in economic development or to acquiescence. Geographical differences in scale variances and mean levels were replicated, with Europeans and Americans generally scoring higher in Extraversion than Asians and Africans. Findings support the rough scalar equivalence of NEO-PI-R factors and facets across cultures, and suggest that aggregate personality profiles provide insight into cultural differences

EFECTIVIDAD DE LOS SISTEMAS DE MEMORIA ORGANIZACIONAL DE UNA INSTITUCIÓN DE EDUCACIÓN SUPERIOR

La memoria organizacional es el medio por el cual el conocimiento del pasado es usado en las actividades actuales. Los sistemas de memoria organizacional (SMO) basados en computador son un tipo de memoria organizacional con soporte tecnológico que ayudan a explicitar el conocimiento. Por lo anterior, el presente artículo es una investigación cualitativa, que centra su estudio en los SMO; para ello, se realizaron entrevistas semiestructuradas a los docentes de la Universidad Técnica Particular de Loja (UTPL), Ecuador, con el objetivo de evaluar la efectividad de esos sistemas utilizados en las actividades académicas. Fue confirmado que los profesores para esa evaluación consideraron los contenidos, estructura y los procesos operativos de recolección, mantenimiento y acceso al conocimiento. Otros resultados encontrados son el soporte de los contenidos para el proceso enseñanza aprendizaje; el formato de los contenidos y la difusión de los sistemas dentro de la organización

Efectividad de los sistemas de memoria organizacional de una institución de educación superior / Effectiveness of organizational memory systems in a higher education institution

La memoria organizacional es el medio por el cual el conocimiento del pasado es usado en las actividades actuales. Los sistemas de memoria organizacional (SMO) basados en computador son un tipo de memoria organizacional con soporte tecnológico que ayudan a explicitar el conocimiento. Por lo anterior, el presente artículo es una investigación cualitativa, que centra su estudio en los SMO; para ello, se realizaron entrevistas semiestructuradas a los docentes de la Universidad Técnica Particular de Loja (UTPL), Ecuador, con el objetivo de evaluar la efectividad de esos sistemas utilizados en las actividades académicas. Fue confirmado que los profesores para esa evaluación consideraron los contenidos, estructura y los procesos operativos de recolección, mantenimiento y acceso al conocimiento. Otros resultados encontrados son el soporte de los contenidos para el proceso enseñanza aprendizaje; el formato de los contenidos y la difusión de los sistemas dentro de la organización.   Organizational memory is the means by which past knowledge can be used in current activities. Organizational Memory Systems (OMS), which are computer-based, are a type of organizational memory with technological support that aims to make knowledge more explicit. This article is a qualitative research study that focuses primarily on OMS. To this end, some semi-structured interviews were carried out with professors from the Universidad Técnica Particular de Loja (UTPL), Ecuador, that is, with the aim of evaluating the effectiveness of the systems that are used in academic activities. It was confirmed that for this evaluation the UTPL professors considered contents, structure and operative processes like collecting, maintaining and accessing knowledge. Other results obtained from this study were content support for the teaching-learning process, content format, and the diffusion of the OMS within an organization

Comparison of MetaMap and cTAKES for entity extraction in clinical notes

Abstract Background Clinical notes such as discharge summaries have a semi- or unstructured format. These documents contain information about diseases, treatments, drugs, etc. Extracting meaningful information from them becomes challenging due to their narrative format. In this context, we aimed to compare the automatic extraction capacity of medical entities using two tools: MetaMap and cTAKES. Methods We worked with i2b2 (Informatics for Integrating Biology to the Bedside) Obesity Challenge data. Two experiments were constructed. In the first one, only one UMLS concept related with the diseases annotated was extracted. In the second, some UMLS concepts were aggregated. Results Results were evaluated with manually annotated medical entities. With the aggregation process the result shows a better improvement. MetaMap had an average of 0.88 in recall, 0.89 in precision, and 0.88 in F-score. With cTAKES, the average of recall, precision and F-score were 0.91, 0.89, and 0.89, respectively. Conclusions The aggregation of concepts (with similar and different semantic types) was shown to be a good strategy for improving the extraction of medical entities, and automatic aggregation could be considered in future works