Identifying the Perceived Severity of Patient-Generated Telemedical Queries Regarding COVID: Developing and Evaluating a Transfer Learning-Based Solution

Abstract

Triage of textual telemedical queries is a safety-critical task for medical service providers with limited remote health resources. The prioritization of patient queries containing medically severe text is necessary to optimize resource usage and provide care to those with time-sensitive needs.

Parker Seegmiller

Innovation Fellow, PhD Candidate @ Dartmouth CS | Applied Science Intern @ Amazon

nlp @ dartmouth college