MedT5SQL: a transformers-based large language model for text-to-SQL conversion in the healthcare domain.

ABSTRACT:

Introduction

In response to the increasing prevalence of electronic medical records (EMRs) stored in databases, healthcare staff are encountering difficulties retrieving these records due to their limited technical expertise in database operations. As these records are crucial for delivering appropriate medical care, there is a need for an accessible method for healthcare staff to access EMRs.

Methods

To address this, natural language processing (NLP) for Text-to-SQL has emerged as a solution, enabling non-technical users to generate SQL queries using natural language text. This research assesses existing work on Text-to-SQL conversion and proposes the MedT5SQL model specifically designed for EMR retrieval. The proposed model utilizes the Text-to-Text Transfer Transformer (T

SUBMITTER: Marshan A 

PROVIDER: S-EPMC11233734 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature