Literature DB >> 24858706

Current and future applications of natural language processing in the field of digestive diseases.

Jason K Hou1, Timothy D Imler2, Thomas F Imperiale3.   

Abstract

Natural language processing (NLP) is a technology that uses computer-based linguistics and artificial intelligence to identify and extract information from free-text data sources such as progress notes, procedure and pathology reports, and laboratory and radiologic test results. With the creation of large databases and the trajectory of health care reform, NLP holds the promise of enhancing the availability, quality, and utility of clinical information with the goal of improving documentation, quality, and efficiency of health care in the United States. To date, NLP has shown promise in automatically determining appropriate colonoscopy intervals and identifying cases of inflammatory bowel disease from electronic health records. The objectives of this review are to provide background on NLP and its associated terminology, to describe how NLP has been used thus far in the field of digestive diseases, and to identify its potential future uses.
Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Adenoma Detection Rate; Clinical Decision Support; Colonoscopy; Inflammatory Bowel Disease; Natural Language Processing; Performance Measures; Quality Improvement

Mesh:

Year:  2014        PMID: 24858706     DOI: 10.1016/j.cgh.2014.05.013

Source DB:  PubMed          Journal:  Clin Gastroenterol Hepatol        ISSN: 1542-3565            Impact factor:   11.382


  7 in total

1.  Multi-center colonoscopy quality measurement utilizing natural language processing.

Authors:  Timothy D Imler; Justin Morea; Charles Kahi; Eric A Sherer; Jon Cardwell; Cynthia S Johnson; Huiping Xu; Dennis Ahnen; Fadi Antaki; Christopher Ashley; Gyorgy Baffy; Ilseung Cho; Jason Dominitz; Jason Hou; Mark Korsten; Anil Nagar; Kittichai Promrat; Douglas Robertson; Sameer Saini; Amandeep Shergill; Walter Smalley; Thomas F Imperiale
Journal:  Am J Gastroenterol       Date:  2015-03-10       Impact factor: 10.864

2.  Natural language processing to ascertain two key variables from operative reports in ophthalmology.

Authors:  Liyan Liu; Neal H Shorstein; Laura B Amsden; Lisa J Herrinton
Journal:  Pharmacoepidemiol Drug Saf       Date:  2017-01-03       Impact factor: 2.890

Review 3.  Importance of determining indication for colonoscopy: implications for practice and policy original.

Authors:  Amit G Singal; Samir Gupta; Jeffrey Lee; Ethan A Halm; Carolyn M Rutter; Douglas Corley; John Inadomi
Journal:  Clin Gastroenterol Hepatol       Date:  2014-12       Impact factor: 11.382

4.  Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

Authors:  Joseph S Redman; Yamini Natarajan; Jason K Hou; Jingqi Wang; Muzammil Hanif; Hua Feng; Jennifer R Kramer; Roxanne Desiderio; Hua Xu; Hashem B El-Serag; Fasiha Kanwal
Journal:  Dig Dis Sci       Date:  2017-08-31       Impact factor: 3.199

5.  Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Authors:  Gottumukkala S Raju; Phillip J Lum; Rebecca S Slack; Selvi Thirumurthi; Patrick M Lynch; Ethan Miller; Brian R Weston; Marta L Davila; Manoop S Bhutani; Mehnaz A Shafi; Robert S Bresalier; Alexander A Dekovich; Jeffrey H Lee; Sushovan Guha; Mala Pande; Boris Blechacz; Asif Rashid; Mark Routbort; Gladis Shuttlesworth; Lopa Mishra; John R Stroehlein; William A Ross
Journal:  Gastrointest Endosc       Date:  2015-04-22       Impact factor: 9.427

Review 6.  What Can We Do to Optimize Colonoscopy and How Effective Can We Be?

Authors:  Kelli S Hancock; Ranjan Mascarenhas; David Lieberman
Journal:  Curr Gastroenterol Rep       Date:  2016-06

7.  Challenges in adapting existing clinical natural language processing systems to multiple, diverse health care settings.

Authors:  David S Carrell; Robert E Schoen; Daniel A Leffler; Michele Morris; Sherri Rose; Andrew Baer; Seth D Crockett; Rebecca A Gourevitch; Katie M Dean; Ateev Mehrotra
Journal:  J Am Med Inform Assoc       Date:  2017-09-01       Impact factor: 4.497

  7 in total

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