ConSore, the medical search engine dedicated to cancer

Digital health, big data technology in the fight against cancer

Coexya implemented the innovative solution ConSoRe, for the Unicancer, Federation of Centers for the Fight Against Cancer in France.  ConSoRe is an evolved tool for semantic search, associated with a Clinical Data Warehouse (CDW), enhancing the use of patients’ data in oncology.

Caregivers and researchers can now quickly and easily assess the feasibility of a therapeutic trial program by querying data from all IS applications using our semantic search engine. The research covers tens of millions of documents, with the possibility to extend the query synchronously to other Centers. Patient cohorts can easily be formed in multiple centers through local or federated searches.

 

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We have implemented a search engine which permit to quickly access documents and data from different applications from a single interface. Within two months, we indexed 500,000 documents, coming from 17 different sources that we have made available to 5000 users.

The tool is based on Natural Language Processing (NLP) components (extraction of medical concepts, morphosyntactic analysis, Machine Learning) to understand the content of documents and automatically summarise patient records.

This is ConSoRe’s strength.

 

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Discover Consore




Discover Consore
This video showcases a demonstration of Consore, a powerful search tool for creating patient cohorts.
This tool leverages data from Cancer Centres, enabling the formation of patient cohorts within a single establishment, as well as performing counts on a national scale by querying other Cancer Centres.
Its strength lies in its ability to process multi-format data (both structured and unstructured), allowing for searches based on multifactorial criteria.

Achievements :

  • Requirements gathering,
  • Architecture and design,
  • Solution integration (data recovery – connector parameterization, data coupling, taking into account IS differences between CLCCs),
  • Implementation of standardized repositories,
  • Data processing (standardization, language analysis, semantic enrichment),
  • Data indexing at center level,
  • Implementation of local search portal,
  • Extend searches to other centers