Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care

Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care

Bibliographic Details
Main Author: Walker, Briana Shanise
Language:English
Published: Case Western Reserve University School of Graduate Studies / OhioLINK 2017
Subjects:
Bioinformatics
Nursing
critical care
transfer of care
text classification
document classification
supervised classification
dialogue
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-case14967600378275372021-08-03T07:02:43Z Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care Walker, Briana Shanise Bioinformatics Nursing critical care transfer of care text classification document classification supervised classification dialogue The research efforts undertaken in this thesis project represent an extension of the previously published works of Alfes & Reimer (2016). This pilot study evaluates the feasibility of applying supervised text classification to properly label successful patient handoffs. Using an expertly-created evaluation rubric as the gold standard for labeling, a variety of document classification techniques were applied to the transcribed dialogue of the Lead Flight specialist in LifeFlight simulation exercises. The purpose of the present work was to establish the effectiveness of the selected classification methods as part of natural language processing algorithm development to automatically identifying handoffs as successful/unsuccessful. Several different common preprocessing filtering methods and text classifiers were selected from the literature and are investigated. The results of the current research indicate that lowercasing tokens, TF-IDF transformation, and normalization of document length can have positive effects on the resulting F1 evaluation metric. Results from the classification test runs indicate that the best performing classifier varies with increasing n-fold cross validation, with Decision Trees (2-,3-fold) and Multinomial Naive Bayes (5-fold) yielding top F1-measures. 2017-06-09 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537 http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Bioinformatics
Nursing
critical care
transfer of care
text classification
document classification
supervised classification
dialogue
spellingShingle Bioinformatics
Nursing
critical care
transfer of care
text classification
document classification
supervised classification
dialogue
Walker, Briana Shanise
Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
author Walker, Briana Shanise
author_facet Walker, Briana Shanise
author_sort Walker, Briana Shanise
title Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
title_short Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
title_full Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
title_fullStr Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
title_full_unstemmed Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care
title_sort rethinking document classification: a pilot for the application of text mining techniques to enhance standardized assessment protocols for critical care medical team transfer of care
publisher Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate 2017
url http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537
work_keys_str_mv AT walkerbrianashanise rethinkingdocumentclassificationapilotfortheapplicationoftextminingtechniquestoenhancestandardizedassessmentprotocolsforcriticalcaremedicalteamtransferofcare
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