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Related Experiment Video

Updated: May 29, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Roogle: an information retrieval engine for clinical data warehouse.

Marc Cuggia1, Nicolas Garcelon, Boris Campillo-Gimenez

  • 1UMR 936 Inserm, Faculté de Médicine de Rennes, France.

Studies in Health Technology and Informatics
|September 7, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces R-oogle, an information retrieval system for electronic patient records. It enables clinicians to efficiently search medical reports using semantic and full-text methods.

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Last Updated: May 29, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

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Published on: September 20, 2018

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09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

  • Medical Informatics
  • Clinical Data Management
  • Information Retrieval

Background:

  • Electronic patient records (EPR) contain vast amounts of valuable clinical information.
  • Accessing and utilizing this information for clinical and research purposes remains a challenge.
  • Existing systems often lack efficient search capabilities tailored for clinical needs.

Purpose of the Study:

  • To develop an information retrieval (IR) system, R-oogle, specifically designed for clinicians.
  • To enable efficient searching of full-text clinical reports and associated metadata.
  • To support applications such as biomarker identification, cohort building, and quality assessment.

Main Methods:

  • Integration of a data warehouse containing full-text reports and structured data from two hospital information systems.
  • Implementation of metadata-based semantic search functionalities.
  • Incorporation of full-text search capabilities, analogous to search engines like Google.

Main Results:

  • The R-oogle system provides a robust platform for accessing and analyzing clinical data.
  • Demonstrated potential for identifying biomarkers through translational research approaches.
  • Facilitates the constitution of patient cohorts for clinical studies and evaluations.

Conclusions:

  • The R-oogle project successfully developed an advanced information retrieval engine for clinical reports.
  • The system enhances the utility of electronic patient records for diverse clinical applications.
  • R-oogle supports data-driven improvements in clinical practice, research, and quality control.