COVID-19 RESOURCES by QUINTELLIGENCE Since late 2016, Quintelligence initiated efforts to refocus and develop text mining and data analytics technologies aiming to provide meaningful ICT tools to decision-making over Big Data in the context of Public Health and Healthcare. The core data sources utilized by these tools are (i) worldwide news articles, through the Event Registry engine; and (ii) the biomedical research over scientific articles in MEDLINE/PubMed. During the pandemic in early 2020, we have refocused some tools developed by our partners at the Jozef Stefan Institute, and build others to address problems as a contribution to the global fight against COVID-19 (read more about it). This work is in line with the global effort of WHO and the recent release of the news monitoring dashboard originating from the initiative of the UNESCO Research Centre for Artificial Intelligence (IRCAI). These tools allow the users to explore the worldwide media, configuring the topic to be monitored over a real-time news stream over 100 thousand news articles daily. Side-by-side it enables health professionals to explore the biomedical research open dataset MEDLINE, that feeds the well-established and worldwide adopted medical science search engine PubMed. MEDLINE EXPLORER
The technology is published Open Source under a BSD license. Repository https://github.com/quintelligence-health/medline-widget Demonstrator https://qmidas.quintelligence.com/searchpoint MESH CLASSIFIER This tool developed aims to classify free text with the latest MeSH Headings provided by NHS. It is based on the DMOZ classifier, learning over 80+ years of MEDLINE data, and over the MeSH tree with 16 major categories and a max of 13 levels of deepness. It provides all the classifying categories with position number and (cosine) similarity weight, with a slider and a number of max categories visible. It available through a web app and an API.
The technology is published Open Source under an Apache 2.0 license. Repository https://github.com/quintelligence-health/medline_classifier Demonstrator https://qmidas.quintelligence.com/classify-mesh-major/ . MEDLINE DASHBOARD ![]() The Kibana dashboard permits the user to profit of data visualization modules that feed on his/her datasets built in ElasticSearch. This tool enables one to query the dataset and produce different types of data visualization modules that can later integrate a customized dashboard. Kibana can be used in any language with any document set (public or private) that can be indexed, analyzed and v isualized with this approach.
The technology is partially published Open Source under an Apache 2.0 license. Repository https://github.com/quintelligence-health/medline-dashboard Demonstrator ONLY through the MIDAS platform .![]() NEWS EXPLORER This tool allows the user to monitor news topics configured to the specificities that most relate to their public health priorities. In that, they can focus specific locations, subtopics, languages, news categories, etc.
The technology is published Open Source under an Apache 2.0 license. Repository https://github.com/quintelligence-health/news-widget Demonstrator ONLY through the MIDAS platform NEWS DASHBOARD ![]() This dashboard is based on the Event Registry technology, allowing the user to explore different aspects of the worldwide and local news. It offers several visualisation modules that can help detecting insights or analyse the newstream to better avoid bias and fake news.
The technology is only available under a commercial license. Repository Not available Demonstrator http://eventregistry.org/ INFLUENZANET HUBS ![]() This tool serves the Influenzanet partners to explore their own data, based on the elasticsearch technology and on Kibana dashboards. The influenzanet system has been active throughout Europe for more than 15 years, allowing to monitor the behaviour of Influenza-Like-Ilness with the help of online volunteers that fill-in a profile and weekly questionnaires. It will be extended to help monitor COVID-19 throughout Europe. This tool enables one to query the dataset based on the Lucene syntax, and produce different types of data visualization modules that can later integrate a customized dashboard. Kibana can be used in any language with any document set (public or private) that can be indexed, analyzed and visualized with this approach.
The technology is published Open Source under an Apache 2.0 license. Repository https://github.com/quintelligence-health/news-widget Demonstrator ONLY through the Influenzanet platform TOPOLOGICAL DATA ANALYSIS This research is based on the data from Influenzanet and is being applied to understand the behaviour of COVID-19 throughout Europe. It is based on the Topological Data Analysis methodology, which examines the structure of data through the topological structure of data. It allows comparing the evolution of the epidemics through the encoded topology of their incidence time series.
The related technology is published Open Source and the results of the research are state-of-the-art, published throughout several scientific publications. STREAMSTORY ![]() This tool allows for the analysis of dynamical Markov processes, analysing simultaneous time-series through transitions between states. It offers several customisation options and data visualisation modules. The approach using this methodology and technology was developed to analyse the Influenzanet data and is being applied to analyse COVID-19.
The related technology is published Open Source and the results of the research are state-of-the-art, published throughout several scientific publications. Disclaimer: The core system was developed by the AI Lab at the IJS and refocused by Quintelligence within the MIDAS project to analyze the MEDLINE dataset. It can be implemented in premises to work with proprietary data. It is currently available as Open Source under the BSD license. Contributors F. Fuart - J. Costa - L. Stopar - M. Grobelnik - D. Mladenić - M. Karlovac - M. Jermol - G. Leban - E. Novak - I. Novalija - P. Škraba - B. Fortuna - L. Rei - A. Košmerlj - J. Belyaeva ![]() ![]() 3 |