SusannaGeorgeThesis.pdf (2.54 MB)

EMERGENCY MEDICAL SERVICE EMR-DRIVEN CONCEPT EXTRACTION FROM NARRATIVE TEXT

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posted on 05.08.2021, 14:49 by Susanna S GeorgeSusanna S George
Being in the midst of a pandemic with patients having minor symptoms that quickly become fatal to patients with situations like a stemi heart attack, a fatal accident injury, and so on, the importance of medical research to improve speed and efficiency in patient care, has increased. As researchers in the computer domain work hard to use automation in technology in assisting the first responders in the work they do, decreasing the cognitive load on the field crew, time taken for documentation of each patient case and improving accuracy in details of a report has been a priority.
This paper presents an information extraction algorithm that custom engineers certain existing extraction techniques that work on the principles of natural language processing like metamap along with syntactic dependency parser like spacy for analyzing the sentence structure and regular expressions to recurring patterns, to retrieve patient-specific information from medical narratives. These concept value pairs automatically populates the fields of an EMR form which could be reviewed and modified manually if needed. This report can then be reused for various medical and billing purposes related to the patient.

Funding

ECE Department Thesis Scholarship

History

Degree Type

Master of Science in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Campus location

Indianapolis

Advisor/Supervisor/Committee Chair

Brian King

Advisor/Supervisor/Committee co-chair

Xiao Luo

Additional Committee Member 2

Catharine Wyss