Leveraging natural language processing of clinical narratives for phenotype modeling

P Raghavan, AM Lai - Proceedings of the 3rd workshop on Ph. D …, 2010 - dl.acm.org
Proceedings of the 3rd workshop on Ph. D. students in information and …, 2010dl.acm.org
This paper will explore methods for effectively extracting information from clinical narratives.
The proposed research will investigate the application of state of the art natural language
processing techniques to clinical narratives, such as medical admission notes, discharge
summaries, progress notes, and pathology reports to extract information of interest. The
objective of this knowledge discovery task is the ability to generate a chronology of events,
for a given patient, ultimately leading to patient cohort discovery. This in turn facilitates …
This paper will explore methods for effectively extracting information from clinical narratives. The proposed research will investigate the application of state of the art natural language processing techniques to clinical narratives, such as medical admission notes, discharge summaries, progress notes, and pathology reports to extract information of interest. The objective of this knowledge discovery task is the ability to generate a chronology of events, for a given patient, ultimately leading to patient cohort discovery. This in turn facilitates efficient information retrieval and enables patient specific question answering.
The paper details the proposed research problem which spans across areas of information extraction, temporal relation extraction and reasoning, and machine learning with the help of two use case scenarios: 1) Automatic patient accrual for clinical trials and 2) Information retrieval over a biorepository.
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