Coreference resolution on entities and events for hospital discharge summaries
Name
334756441-MIT.pdf
Description
Full printable version
Size
20 MB
Format
Adobe PDF
Checksum (MD5)
041ad8092d3d9ff3aa1a5078930ae6f1
Author(s)
He, Tian Ye
Advisor(s)
Ozlem Uzuner and Peter Szolovits.
Date Issued
2007
Publisher
Massachusetts Institute of Technology
Abstract
The wealth of medical information contained in electronic medical records (EMRs) and Natural Language Processing (NLP) technologies that can automatically extract information from them have opened the doors to automatic patient-care quality monitoring and medical- assist question answering systems. This thesis studies coreference resolution, an information extraction (IE) subtask that links together specific mentions to each entity. Coreference resolution enables us to find changes in the state of entities and makes it possible to answer questions regarding the information thus obtained. We perform coreference resolution on a specific type of EMR, the hospital discharge summary. We treat coreference resolution as a binary classification problem. Our approach yields insights into the critical features for coreference resolution for entities that fall into five medical semantic categories that commonly appear in discharge summaries.
Description
Includes bibliographical references (p. 76-80).
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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