Literature DB >> 21893816

Roogle: an information retrieval engine for clinical data warehouse.

Marc Cuggia1, Nicolas Garcelon, Boris Campillo-Gimenez, Thomas Bernicot, Jean-François Laurent, Etienne Garin, André Happe, Régis Duvauferrier.   

Abstract

High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different hospital information systems. Information retrieval is performed using metadata-based semantic and full-text search methods (as Google). Applications may be biomarkers identification in a translational approach, search of specific cases, and constitution of cohorts, professional practice evaluation, and quality control assessment.

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Mesh:

Year:  2011        PMID: 21893816

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  15 in total

1.  Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm.

Authors:  Thibault Ledieu; Guillaume Bouzille; Catherine Plaisant; Frantz Thiessard; Elisabeth Polard; Marc Cuggia
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  Mapping local laboratory interface terms to LOINC at a German university hospital using RELMA V.5: a semi-automated approach.

Authors:  Christian Zunner; Thomas Bürkle; Hans-Ulrich Prokosch; Thomas Ganslandt
Journal:  J Am Med Inform Assoc       Date:  2012-07-16       Impact factor: 4.497

3.  Reviewing 741 patients records in two hours with FASTVISU.

Authors:  Jean-Baptiste Escudié; Anne-Sophie Jannot; Eric Zapletal; Sarah Cohen; Georgia Malamut; Anita Burgun; Bastien Rance
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

4.  Clinical use of an enterprise data warehouse.

Authors:  R Scott Evans; James F Lloyd; Lee A Pierce
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

5.  Improving a full-text search engine: the importance of negation detection and family history context to identify cases in a biomedical data warehouse.

Authors:  Nicolas Garcelon; Antoine Neuraz; Vincent Benoit; Rémi Salomon; Anita Burgun
Journal:  J Am Med Inform Assoc       Date:  2017-05-01       Impact factor: 4.497

Review 6.  Big data and clinicians: a review on the state of the science.

Authors:  Weiqi Wang; Eswar Krishnan
Journal:  JMIR Med Inform       Date:  2014-01-17

7.  Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records.

Authors:  Emmanuelle Sylvestre; Guillaume Bouzillé; Emmanuel Chazard; Cécil His-Mahier; Christine Riou; Marc Cuggia
Journal:  BMC Med Inform Decis Mak       Date:  2018-01-24       Impact factor: 2.796

Review 8.  Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.

Authors:  Marie-Line Gentil; Marc Cuggia; Laure Fiquet; Camille Hagenbourger; Thomas Le Berre; Agnès Banâtre; Eric Renault; Guillaume Bouzille; Anthony Chapron
Journal:  BMC Med Inform Decis Mak       Date:  2017-09-25       Impact factor: 2.796

9.  Improving case-based reasoning systems by combining k-nearest neighbour algorithm with logistic regression in the prediction of patients' registration on the renal transplant waiting list.

Authors:  Boris Campillo-Gimenez; Wassim Jouini; Sahar Bayat; Marc Cuggia
Journal:  PLoS One       Date:  2013-09-09       Impact factor: 3.240

10.  Timeline representation of clinical data: usability and added value for pharmacovigilance.

Authors:  Thibault Ledieu; Guillaume Bouzillé; Frantz Thiessard; Karine Berquet; Pascal Van Hille; Eric Renault; Elisabeth Polard; Marc Cuggia
Journal:  BMC Med Inform Decis Mak       Date:  2018-10-19       Impact factor: 2.796

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