Literature DB >> 28111640

Identifying Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.

Naveed Afzal1, Sunghwan Sohn1, Sara Abram2, Hongfang Liu1, Iftikhar J Kullo2, Adelaide M Arruda-Olson2.   

Abstract

Peripheral arterial disease (PAD) is a chronic disease that affects millions of people worldwide. Ascertaining PAD status from clinical notes by manual chart review is labor intensive and time consuming. In this paper, we describe a natural language processing (NLP) algorithm for automated ascertainment of PAD status from clinical notes using predetermined criteria. We developed and evaluated our system against a gold standard that was created by medical experts based on manual chart review. Our system ascertained PAD status from clinical notes with high sensitivity (0.96), positive predictive value (0.92), negative predictive value (0.99) and specificity (0.98). NLP approaches can be used for rapid, efficient and automated ascertainment of PAD cases with implications for patient care and epidemiologic research.

Entities:  

Year:  2016        PMID： 28111640      PMCID： PMC5248569          DOI： 10.1109/BHI.2016.7455851

Source DB:  PubMed          Journal:  IEEE EMBS Int Conf Biomed Health Inform        ISSN： 2641-3590


  28 in total

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Journal:  Ann Allergy Asthma Immunol       Date:  2013-08-12       Impact factor: 6.347

6.  Towards a semantic lexicon for clinical natural language processing.

Authors:  Hongfang Liu; Stephen T Wu; Dingcheng Li; Siddhartha Jonnalagadda; Sunghwan Sohn; Kavishwar Wagholikar; Peter J Haug; Stanley M Huff; Christopher G Chute
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  8 in total

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Review 2.  Clinical information extraction applications: A literature review.

Authors:  Yanshan Wang; Liwei Wang; Majid Rastegar-Mojarad; Sungrim Moon; Feichen Shen; Naveed Afzal; Sijia Liu; Yuqun Zeng; Saeed Mehrabi; Sunghwan Sohn; Hongfang Liu
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3.  Surveillance of Peripheral Arterial Disease Cases Using Natural Language Processing of Clinical Notes.

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Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2017-07-26

4.  CUILESS2016: a clinical corpus applying compositional normalization of text mentions.

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5.  Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study.

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6.  Preliminary development of a deep learning-based automated primary headache diagnosis model using Japanese natural language processing of medical questionnaire.

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7.  Usability of a Digital Registry to Promote Secondary Prevention for Peripheral Artery Disease Patients.

Authors:  Alisha P Chaudhry; Ronald A Hankey; Vinod C Kaggal; Huzefa Bhopalwala; David A Liedl; Paul W Wennberg; Thom W Rooke; Christopher G Scott; Magali P Disdier Moulder; Abby K Hendricks; Ana I Casanegra; Robert D McBane; Jane L Shellum; Iftikhar J Kullo; Rick A Nishimura; Rajeev Chaudhry; Adelaide M Arruda-Olson
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8.  Evaluation of a Concept Mapping Task Using Named Entity Recognition and Normalization in Unstructured Clinical Text.

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  8 in total

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