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Yearb Med Inform 2015; 24(01): 183-193
DOI: 10.15265/IY-2015-009
Original Article
Georg Thieme Verlag KG Stuttgart

Recent Advances in Clinical Natural Language Processing in Support of Semantic Analysis

S. Velupillai
1  Department of Computer and Systems Sciences, (DSV), Stockholm University, Stockholm, Sweden
,
D. Mowery
2  Department of Biomedical Informatics, University of Utah, Salt Lake City, USA
,
B. R. South
2  Department of Biomedical Informatics, University of Utah, Salt Lake City, USA
,
M. Kvist
1  Department of Computer and Systems Sciences, (DSV), Stockholm University, Stockholm, Sweden
3  Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Sweden
,
H. Dalianis
1  Department of Computer and Systems Sciences, (DSV), Stockholm University, Stockholm, Sweden
› Author Affiliations
Further Information

Correspondence to:

Sumithra Velupillai
Department of Computer and Systems Sciences
Stockholm University
Postbox 7003
164 07 Kista
Sweden
Phone: +46 8 161 174   
Fax: +46 8 703 9025   

Publication History

13 August 2015

Publication Date:
10 March 2018 (online)

 
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Summary

Objectives: We present a review of recent advances in clinical Natural Language Processing (NLP), with a focus on semantic analysis and key subtasks that support such analysis.

Methods: We conducted a literature review of clinical NLP research from 2008 to 2014, emphasizing recent publications (2012-2014), based on PubMed and ACL proceedings as well as relevant referenced publications from the included papers.

Results: Significant articles published within this time-span were included and are discussed from the perspective of semantic analysis. Three key clinical NLP subtasks that enable such analysis were identified: 1) developing more efficient methods for corpus creation (annotation and de-identification), 2) generating building blocks for extracting meaning (morphological, syntactic, and semantic subtasks), and 3) leveraging NLP for clinical utility (NLP applications and infrastructure for clinical use cases). Finally, we provide a reflection upon most recent developments and potential areas of future NLP development and applications.

Conclusions: There has been an increase of advances within key NLP subtasks that support semantic analysis. Performance of NLP semantic analysis is, in many cases, close to that of agreement between humans. The creation and release of corpora annotated with complex semantic information models has greatly supported the development of new tools and approaches. Research on non-English languages is continuously growing. NLP methods have sometimes been successfully employed in real-world clinical tasks. However, there is still a gap between the development of advanced resources and their utilization in clinical settings. A plethora of new clinical use cases are emerging due to established health care initiatives and additional patient-generated sources through the extensive use of social media and other devices.


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Keywords

Clinical Natural Language Processing - Semantics - Information Extraction - Annotation, Domain Adaptation - Review

 


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Correspondence to:

Sumithra Velupillai
Department of Computer and Systems Sciences
Stockholm University
Postbox 7003
164 07 Kista
Sweden
Phone: +46 8 161 174   
Fax: +46 8 703 9025   


  Permissions and Reprints