MEDLINE MINING
QUINTELLIGENCE  DEMOS




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The portal SearchPoint exhibits the clustered keywords of a query on the MEDLINE/PubMed open dataset, after searching for a keyword. This interactive visual tool helps to surface information we are looking for, avoiding the standard answer that is biased by definition. SearchPoint can be used in any language with any document set (public or private) that can be indexed, analyzed and visualized with this approach.

MIDAS SearchPoint Demo

  • designed to improve the search engine experience; the user provides further information to the search by interacting with the system by dragging a pointer over word clouds
  • these word clouds are produced by cosine similarity to an "average" centred on the topics in each abstract of the set of selected papers, clustered using the k-means algorithm
  • it can be used with any document set (public or private) that can be indexed, analyzed and visualized with this approach. 
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.






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The MeSH Classifier is a tool developed by Quintelligence 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. 


  • designed to classify free text of any nature with the classes of MeSH Headings where MEDLINE is based on, to which health professionals are familiar with  

    MIDAS MeSH Classifier Demo

  • it can classify articles that haven't yet been annotated by the NHS, or official WHO documents of interest
  • it can also classify news articles and be used to monitor worldwide news based on the classification provided at the MeSH Headings  

The core system was developed by the AI Lab at the IJS and refocused by Quintelligence within the MIDAS project to use the MeSH Headings to classify free text. It can be implemented in premises to work with proprietary data. It is currently available as Open Source under the BSD license.








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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 visualized with this approach.


MIDAS ElasticSearch Demo

  • designed to improve the user experience in exploring the MEDLINE dataset through visualization modules composing topic dedicated live monitoring dashboards 
  • the visualization modules based on Kibana do not require technical skills and enable the data exploration by a diversity of professionals
  • the system includes a powerful querying engine based on the open-source information retrieval software library Lucene    

This system was developed by the AI Lab at the IJS and refocused by Quintelligence within the MIDAS project to visually 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.






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