Managing Free Text for Secondary Use of Health Data

N. Griffon; J. Charlet; S. J. Darmoni; Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management

doi:10.15265/IY-2014-0037

Yearbook of Medical Informatics, Table of Contents

Yearb Med Inform 2014; 23(01): 167-169
DOI: 10.15265/IY-2014-0037

Original Article

Georg Thieme Verlag KG Stuttgart

Managing Free Text for Secondary Use of Health Data

Findings from the Yearbook 2014 Section on Knowledge Representation and Management

N. Griffon

¹CISMeF, Rouen University Hospital, Normandy & TIBS, LITIS EA 4108, Institute for Research and Innovation in Biomedicine, Rouen, France

²INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), Villetaneuse, France

,

J. Charlet

²INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), Villetaneuse, France

³AP-HP, Dept. of Clinical Research and Development, Paris, France

,

S. J. Darmoni

¹CISMeF, Rouen University Hospital, Normandy & TIBS, LITIS EA 4108, Institute for Research and Innovation in Biomedicine, Rouen, France

²INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), Villetaneuse, France

,

Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management

› Author Affiliations

Abstract

Summary

Objective: To summarize the best papers in the field of Knowledge Representation and Management (KRM).

Methods: A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM and natural language processing (NLP) published in 2013.

Results: Four articles were selected, one focuses on Electronic Health Record (EHR) interoperability for clinical pathway personalization based on structured data. The other three focus on NLP (corpus creation, de-identification, and co-reference resolution) and highlight the increase in NLP tools performances.

Conclusion: NLP tools are close to being seriously concurrent to humans in some annotation tasks. Their use could increase drastically the amount of data usable for meaningful use of EHR.

Keywords

Medical informatics - knowledge representation - natural language processing - semantic web - ontology

Full Text

References

References
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