GPT-Based Model for Concise Summaries of Patient Health Information.

Abstract

Although Patient Health Records (PHRs) are vital tools for patients, enabling them to access and manage health information, it remains challenging for doctors and patients to gather a swift overview of a patient's health status based on the extensive information included in the PHR. Our study introduces a generative pre-trained transformer-based language model to summarize health information documented in previously developed PHRs efficiently. By fine-tuning the model, we achieved results comparable to those of other studies in this domain, despite utilizing a smaller dataset. This data-to-text application represents a novel method that can be expected to promote enhanced information management in the medical field.