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Robust Methods for Clinical Text Classification and Disease Understanding With NLP Extracted Symptoms From Clinical Notes.
ข้อมูลเนื้อหา
Robust Methods for Clinical Text Classification and Disease Understanding With NLP Extracted Symptoms From Clinical Notes.
자료유형  
 학위논문
Control Number  
0017163080
International Standard Book Number  
9798384094524
Dewey Decimal Classification Number  
020
Main Entry-Personal Name  
Zhou, Weipeng.
Publication, Distribution, etc. (Imprint  
[S.l.] : University of Washington., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
134 p.
General Note  
Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
General Note  
Advisor: Yetisgen, Meliha.
Dissertation Note  
Thesis (Ph.D.)--University of Washington, 2024.
Summary, Etc.  
요약Electronic Health Records (EHR) contain comprehensive medical and treatment histories of patients and have the potential to be used to provide better healthcare. A significant portion of the EHR is in the form of clinical notes and Natural Language Processing (NLP) methods can help extract hidden information from them. However, applying NLP in healthcare has challenges. Many of the clinical note datasets are scarce and imbalanced, making it difficult to develop generalizable and robust NLP methods. Additionally, effective use of NLP in healthcare requires close collaboration with medical experts to identify and understand meaningful clinical problems. This dissertation addresses these challenges and explores the application of NLP in healthcare. In Chapter 3 and 4, we develop generalizable and robust NLP methods for clinical note classification and female suicide report coding. In Chapter 5 and 6, we apply NLP to extract symptoms from clinical notes and study risk factors associated with out-of-hospital cardiac arrest (OHCA) and Long COVID.
Subject Added Entry-Topical Term  
Information science.
Subject Added Entry-Topical Term  
Computer science.
Subject Added Entry-Topical Term  
Medicine.
Subject Added Entry-Topical Term  
Bioinformatics.
Index Term-Uncontrolled  
Electronic Health Records
Index Term-Uncontrolled  
Natural Language Processing
Index Term-Uncontrolled  
Out-of-hospital cardiac arrest
Index Term-Uncontrolled  
Clinical notes
Added Entry-Corporate Name  
University of Washington Biomedical Informatics and Medical Education
Host Item Entry  
Dissertations Abstracts International. 86-03B.
Electronic Location and Access  
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Control Number  
joongbu:657278
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