MODELO PARA EL ANÁLISIS DE SENTIMIENTOS DEL BANCO DE ENCUESTAS CON PREGUNTAS SOBRE CORONAVIRUS DE LA OMS EMPLEANDO PRINCIPIOS DE MINERÍA DE TEXTOS

La presente investigación tiene la finalidad de elaborar un modelo de Análisis de Sentimientos de un Banco de 250 instrumentos de recolección de Datos sobre Coronavirus, mismo que es guardado como referencia en el sitio web oficial de la Organización Mundial de la Salud, OMS. Para esto se ha empleado fundamentos de Minería de Textos mediante la plataforma Open Source de Minería de Datos, Orange, construyendo un modelo que analiza el Corpus de documentos y genera diagramas de distribución de sentimientos según la herramienta Valence Aware Dictionary and Sentiment Reasoner, VADER, y nube de palabras que ilustra el peso de las palabras según su frecuencia en el Corpus. Los resultados reflejan que las emociones Neutras son las que alcanzan valores más altos en todos los tipos de preguntas, las Negativas y Positivas guardan cierto patrón y alcanzan niveles medios en todos los tipos de preguntas, en tanto que las emociones Combinadas no tienen un patrón establecido, aunque son más frecuentes en preguntas relacionadas al Entorno, Conocimiento y Tratamiento de Salud de los posibles encuestados. Es de indicar que los tipos de preguntas son siete: Entorno, Exposición, Impacto, Conocimiento, Atención médica, Percepción y Miscelánea.PALABRAS CLAVE: Big Data; Minería de Datos; Orange; Minería de Textos; Coronavirus.MODEL FOR THE ANALYSIS OF FEELINGS OF THE SURVEY BANK WITH QUESTIONS ON WHO CORONAVIRUSES USING TEXT MINING PRINCIPLESABSTRACTThis is an academic paper, the purpose of which is to develop a Sentiment Analysis model of a Bank of 250 instruments for data collection on Coronavirus, which is kept as a reference on the official website of the World Health Organization, WHO . For this, Text Mining fundamentals have been used through the Open Source Data Mining platform, Orange, building a model that analyzes the Corpus of documents and generates diagrams of sentiment distribution according to the Valence Aware Dictionary and Sentiment Reasoner tool, VADER, and word cloud that illustrates the weight of words according to their frequency in Corpus. The results reflect that the Neutral emotions are those that reach higher values in all types of questions, the Negative and Positive ones maintain a certain pattern and reach medium levels in all types of questions, while the Combined emotions do not have an established pattern , although they are more frequent in questions related to the Environment, Knowledge and Treatment of Health of the possible respondents. It is to indicate that the types of questions are seven: Environment, Exposure, Impact, Knowledge, Medical attention, Perception and Miscellaneous.KEYWORDS: Big Data; Data Mining; Orange; Text Mining; Coronavirus

Global attitudes in the management of acute appendicitis during COVID-19 pandemic: ACIE Appy Study

Background: Surgical strategies are being adapted to face the COVID-19 pandemic. Recommendations on the management of acute appendicitis have been based on expert opinion, but very little evidence is available. This study addressed that dearth with a snapshot of worldwide approaches to appendicitis. Methods: The Association of Italian Surgeons in Europe designed an online survey to assess the current attitude of surgeons globally regarding the management of patients with acute appendicitis during the pandemic. Questions were divided into baseline information, hospital organization and screening, personal protective equipment, management and surgical approach, and patient presentation before versus during the pandemic. Results: Of 744 answers, 709 (from 66 countries) were complete and were included in the analysis. Most hospitals were treating both patients with and those without COVID. There was variation in screening indications and modality used, with chest X-ray plus molecular testing (PCR) being the commonest (19\ub78 per cent). Conservative management of complicated and uncomplicated appendicitis was used by 6\ub76 and 2\ub74 per cent respectively before, but 23\ub77 and 5\ub73 per cent, during the pandemic (both P < 0\ub7001). One-third changed their approach from laparoscopic to open surgery owing to the popular (but evidence-lacking) advice from expert groups during the initial phase of the pandemic. No agreement on how to filter surgical smoke plume during laparoscopy was identified. There was an overall reduction in the number of patients admitted with appendicitis and one-third felt that patients who did present had more severe appendicitis than they usually observe. Conclusion: Conservative management of mild appendicitis has been possible during the pandemic. The fact that some surgeons switched to open appendicectomy may reflect the poor guidelines that emanated in the early phase of SARS-CoV-2