Literature DB >> 28423797

HTP-NLP: A New NLP System for High Throughput Phenotyping.

Daniel R Schlegel1, Chris Crowner2, Frank Lehoullier2, Peter L Elkin2.   

Abstract

Secondary use of clinical data for research requires a method to quickly process the data so that researchers can quickly extract cohorts. We present two advances in the High Throughput Phenotyping NLP system which support the aim of truly high throughput processing of clinical data, inspired by a characterization of the linguistic properties of such data. Semantic indexing to store and generalize partially-processed results and the use of compositional expressions for ungrammatical text are discussed, along with a set of initial timing results for the system.

Entities:  

Keywords:  clinical NLP; compositional expressions; high throughput phenotyping

Mesh：

Year:  2017        PMID： 28423797      PMCID： PMC7767581     

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN： 0926-9630


  8 in total

1.  Guideline for health informatics: controlled health vocabularies--vocabulary structure and high-level indicators.

Authors:  P L Elkin; S H Brown; C G Chute
Journal:  Stud Health Technol Inform       Date:  2001

2.  Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.

Authors:  Guergana K Savova; James J Masanz; Philip V Ogren; Jiaping Zheng; Sunghwan Sohn; Karin C Kipper-Schuler; Christopher G Chute
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

3.  Automatically Expanding the Synonym Set of SNOMED CT using Wikipedia.

Authors:  Daniel R Schlegel; Chris Crowner; Peter L Elkin
Journal:  Stud Health Technol Inform       Date:  2015

4.  PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.

Authors:  Jacqueline C Kirby; Peter Speltz; Luke V Rasmussen; Melissa Basford; Omri Gottesman; Peggy L Peissig; Jennifer A Pacheco; Gerard Tromp; Jyotishman Pathak; David S Carrell; Stephen B Ellis; Todd Lingren; Will K Thompson; Guergana Savova; Jonathan Haines; Dan M Roden; Paul A Harris; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2016-03-28       Impact factor: 4.497

5.  Evaluation of the content coverage of SNOMED CT: ability of SNOMED clinical terms to represent clinical problem lists.

Authors:  Peter L Elkin; Steven H Brown; Casey S Husser; Brent A Bauer; Dietlind Wahner-Roedler; S Trent Rosenbloom; Ted Speroff
Journal:  Mayo Clin Proc       Date:  2006-06       Impact factor: 7.616

6.  Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

Authors:  Sheng Yu; Katherine P Liao; Stanley Y Shaw; Vivian S Gainer; Susanne E Churchill; Peter Szolovits; Shawn N Murphy; Isaac S Kohane; Tianxi Cai
Journal:  J Am Med Inform Assoc       Date:  2015-04-29       Impact factor: 4.497

7.  eQuality: electronic quality assessment from narrative clinical reports.

Authors:  Steven H Brown; Theodore Speroff; Elliot M Fielstein; Brent A Bauer; Dietlind L Wahner-Roedler; Robert Greevy; Peter L Elkin
Journal:  Mayo Clin Proc       Date:  2006-11       Impact factor: 7.616

8.  Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium.

Authors:  Jyotishman Pathak; Kent R Bailey; Calvin E Beebe; Steven Bethard; David C Carrell; Pei J Chen; Dmitriy Dligach; Cory M Endle; Lacey A Hart; Peter J Haug; Stanley M Huff; Vinod C Kaggal; Dingcheng Li; Hongfang Liu; Kyle Marchant; James Masanz; Timothy Miller; Thomas A Oniki; Martha Palmer; Kevin J Peterson; Susan Rea; Guergana K Savova; Craig R Stancl; Sunghwan Sohn; Harold R Solbrig; Dale B Suesse; Cui Tao; David P Taylor; Les Westberg; Stephen Wu; Ning Zhuo; Christopher G Chute
Journal:  J Am Med Inform Assoc       Date:  2013-11-04       Impact factor: 4.497
  8 in total
  9 in total

1.  Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies.

Authors:  Majid Afshar; Dmitriy Dligach; Brihat Sharma; Xiaoyuan Cai; Jason Boyda; Steven Birch; Daniel Valdez; Suzan Zelisko; Cara Joyce; François Modave; Ron Price
Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

2.  Secondary Use of EHR: Interpreting Clinician Inter-Rater Reliability Through Qualitative Assessment.

Authors:  Sarah Mullin; Edwin Anand; Shyamashree Sinha; Buer Song; Jane Zhao; Peter L Elkin
Journal:  Stud Health Technol Inform       Date:  2017

3.  Clinical Tractor: A Framework for Automatic Natural Language Understanding of Clinical Practice Guidelines.

Authors:  Daniel R Schlegel; Kate Gordon; Carmelo Gaudioso; Mor Peleg
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

4.  Automated Modeling of Clinical Narrative with High Definition Natural Language Processing Using Solor and Analysis Normal Form.

Authors:  Melissa P Resnick; Frank LeHouillier; Steven H Brown; Keith E Campbell; Diane Montella; Peter L Elkin
Journal:  Stud Health Technol Inform       Date:  2021-11-18

5.  Biomedical Informatics Investigator.

Authors:  Peter L Elkin; Sarah Mullin; Sylvester Sakilay
Journal:  Stud Health Technol Inform       Date:  2018

6.  Rosacea Patients Are at Higher Risk for Obstructive Sleep Apnea: Automated Retrospective Research.

Authors:  Peter L Elkin; Sarah Mullin; Sylvester Sakilay
Journal:  Stud Health Technol Inform       Date:  2020-06-16

7.  Sustainable Health Informatics: Health Informaticians as Alchemists.

Authors:  Christian Nøhr; Craig E Kuziemsky; Peter L Elkin; Romaric Marcilly; Sylvia Pelayo
Journal:  Stud Health Technol Inform       Date:  2019-08-09

8.  Use of the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for Processing Free Text in Health Care: Systematic Scoping Review.

Authors:  Christophe Gaudet-Blavignac; Vasiliki Foufi; Mina Bjelogrlic; Christian Lovis
Journal:  J Med Internet Res       Date:  2021-01-26       Impact factor: 5.428

9.  Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record's Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study.

Authors:  Peter L Elkin; Sarah Mullin; Jack Mardekian; Christopher Crowner; Sylvester Sakilay; Shyamashree Sinha; Gary Brady; Marcia Wright; Kimberly Nolen; JoAnn Trainer; Ross Koppel; Daniel Schlegel; Sashank Kaushik; Jane Zhao; Buer Song; Edwin Anand
Journal:  J Med Internet Res       Date:  2021-11-09       Impact factor: 5.428
  9 in total

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