Named entity recognition of follow-up and time information in 20 000 radiology reports

Xu Y et al, J Am Med Inform Assoc, 2012

Objective
To develop a system to extract follow-up information from radiology reports. The method may be used as a component in a system which automatically generates follow-up information in a timely fashion.

Methods
A novel method of combining an LSP (labeled sequential pattern) classifier with a CRF (conditional random field) recognizer was devised. The LSP classifier filters out irrelevant sentences, while the CRF recognizer extracts follow-up and time phrases from candidate sentences presented by the LSP classifier.
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11 July 2012 | No Comments »
Categories: Bibliography, Journal Article | Keyword(s): Data Extraction, Electronic Health Records, Radiology, United States

Exploring the Ability of Natural Language Processing to Extract Data From Nursing Narratives

Hyun, Sookyung et al, Computers Informatics Nursing, 27(4)

Natural Language Processing (NLP) offers an approach for capturing data from narratives and creating structured reports for further computer processing. We explored the ability of a NLP system, Medical Language Extraction and Encoding (MedLEE), on nursing narratives. MedLEE extracted 490 concepts from narrative text in a sample of 553 oncology nursing process notes.
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4 July 2009 | No Comments »
Categories: Journal Article | Keyword(s): Data Capture, Data Extraction, Narrative, NLP, Oncology, Patient Safety, Quality