A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Disseny i implementació d'un sistema web de geolocalització i promoció d'events

Degut a la falta d'informació, de temps, no saber a on buscar. . . moltes vegades no ens assabentem, o ho fem massa tard, d'events als que ens hauria agradat assistir, com podrien ser concerts,conferències, activitats esportives, etc. L'objectiu d'aquest projecte serà aprofitar les capacitats de les xarxes socials per crear un lloc web que permeti enviar i geolocalitzar events que podran ser revisats i promoguts pels usuaris, de forma que es pugui suplir aquesta mancança. La solució implementada haurà de proporcionar les següents funcionalitats: enviament d'events (permetrà afegir les dades principals d'un event i geolocalitzar-lo en el mapa); organització de la informació (es disposarà de categories i metacategories per agrupar els events, a més d'un sistema d'etiquetes que facilitarà les cerques en el contingut del web); exploració dels events existents (mitjançant el mapa es podrà veure les dades de qualsevol event); sistema de votació (atorgarà la capacitat per poder decidir quina informació és més rellevant); agenda personal (servirà per registrar events i d'aquesta manera poder rebre notificacions que informin de canvis o simplement que serveixin com a recordatori); comunicació entre usuaris (es realitzarà a través de comentaris al peu dels events i/o d'un xat intern); sindicació web (distribuirà el contingut utilitzant l'estàndard RSS; disponibilitat d'una API simple (permetrà l'accés a certa informació des d'aplicacions externes)

A survey on voltage sag events in power systems

This paper aims to survey the techniques and methods described in literature to analyse and characterise voltage sags and the corresponding objectives of these works. The study has been performed from a data mining point of view

Mining Events from Multimedia streams, Jon Hare

peaker(s): Jon Hare Organiser: Time: 25/06/2014 11:00-11:50 Location: B32/3077 Abstract The aggregation of items from social media streams, such as Flickr photos and Twitter tweets, into meaningful groups can help users contextualise and effectively consume the torrents of information on the social web. This task is challenging due to the scale of the streams and the inherently multimodal nature of the information being contextualised. In this talk I'll describe some of our recent work on trend and event detection in multimedia data streams. We focus on scalable streaming algorithms that can be applied to multimedia data streams from the web and the social web. The talk will cover two particular aspects of our work: mining Twitter for trending images by detecting near duplicates; and detecting social events in multimedia data with streaming clustering algorithms. I'll will describe in detail our techniques, and explore open questions and areas of potential future work, in both these tasks.

Autobiographical Memory for Stressful Events, Traumatic Memory and Posttraumatic Stress Disorder: A Systematic Review

Stressors and traumatic events may contribute to the development of many psychopathologies, PTSD among them. People with this disorder can present significant cognitive impairments and losses in memory, particularly autobiographical memory (AM).This paper aims to present a systematic review of literature considering changes on autobiographical memory in people exposed to potentially traumatic stressors. Therefore, we performed a computerized search in databases PsycINFO, PubMed, Web of Science and Pilots in March 2012.A total of 29 articles were selected and grouped into three categories: studies comparing Trauma X PTSD, studies comparing PTSD X Trauma X Control and comparison studies according to post-traumatic symptoms. Results demonstrate that people with PTSD presents alterations in a larger number of AM components compared to the cases in which PTSD did not developed. In the same way, subjects never exposed to trauma did not demonstrate significant alterations on  AM when compared to the other groups. The results of this study allowed concluding that changes of some components of the AM are primarily associated with PTSD, but it was not possible to clarify whether such changes are related to the timely development of the disorder, or if they are also observed in traumatic memories even in the absence of disorder.