Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models.

ABSTRACT:

Objectives

The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care.

Materials and methods

We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-c

SUBMITTER: Ren Y 

PROVIDER: S-EPMC11258404 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature