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Full-Text Articles in Bioinformatics
Disease Name Extraction From Clinical Text Using Conditional Random Fields, Omid Ghiasvand
Disease Name Extraction From Clinical Text Using Conditional Random Fields, Omid Ghiasvand
Theses and Dissertations
The aim of the research done in this thesis was to extract disease and disorder names from clinical texts. We utilized Conditional Random Fields (CRF) as the main method to label diseases and disorders in clinical sentences. We used some other tools such as MetaMap and Stanford Core NLP tool to extract some crucial features. MetaMap tool was used to identify names of diseases/disorders that are already in UMLS Metathesaurus. Some other important features such as lemmatized versions of words, and POS tags were extracted using the Stanford Core NLP tool. Some more features were extracted directly from UMLS Metathesaurus, …
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Legacy Theses & Dissertations (2009 - 2024)
Temporal reasoning in natural language refers to the extraction and understanding of time-related information conveyed in free text. A clinical narrative temporal reasoning component can enable a spectrum of medical natural language processing (NLP) applications that directly improve patient care documentation efficiency, accessibility and accountability. This dissertation contributes in three subtasks under temporal reasoning: temporal annotation, temporal expression extraction and temporal relation inferences. The temporal annotation work described in the dissertation produced one of the first publicly available clinical narratives. We published one of the first sets of temporal