Evaluating the comprehension and accuracy of ChatGPT's responses to diabetes-related questions in Urdu compared to English.

ABSTRACT:

Introduction

Patients with diabetes require healthcare and information that are accurate and extensive. Large language models (LLMs) like ChatGPT herald the capacity to provide such exhaustive data. To determine (a) the comprehensiveness of ChatGPT's responses in Urdu to diabetes-related questions and (b) the accuracy of ChatGPT's Urdu responses when compared to its English responses.

Methods

A cross-sectional observational study was conducted. Two reviewers experienced in internal medicine and endocrinology graded 53 Urdu and English responses on diabetes knowledge, lifestyle, and prevention. A senior reviewer resolved discrepancies. Responses were assessed for comprehension and accuracy, then compared to English.

Results

Among the Urdu responses generated, only two

SUBMITTER: Faisal S 

PROVIDER: S-EPMC11490976 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature