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

Nicolas Garcelon | Zendy; Antoine Neuraz | Zendy; Vincent Benoît | Zendy; Rémi Salomon | Zendy; Anita Burgun | Zendy

Open Access

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

Author(s) -

Nicolas Garcelon,

Antoine Neuraz,

Vincent Benoît,

Rémi Salomon,

Anita Burgun

Publication year - 2016

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1093/jamia/ocw144

Subject(s) - pipeline (software) , context (archaeology) , data warehouse , computer science , negation , family history , narrative , electronic health record , repurposing , process (computing) , information retrieval , medicine , artificial intelligence , database , health care , engineering , geography , linguistics , philosophy , archaeology , economic growth , economics , programming language , waste management , operating system

The repurposing of electronic health records (EHRs) can improve clinical and genetic research for rare diseases. However, significant information in rare disease EHRs is embedded in the narrative reports, which contain many negated clinical signs and family medical history. This paper presents a method to detect family history and negation in narrative reports and evaluates its impact on selecting populations from a clinical data warehouse (CDW).

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