Balancing accuracy and user satisfaction: the role of prompt engineering in AI-driven healthcare solutions.

ABSTRACT:

Introduction

The rapid evolution of the Internet of Things (IoT) and Artificial Intelligence (AI) has opened new possibilities for public healthcare. Effective integration of these technologies is essential to ensure precise and efficient healthcare delivery. This study explores the application of IoT-enabled, AI-driven systems for detecting and managing Dry Eye Disease (DED), emphasizing the use of prompt engineering to enhance system performance.

Methods

A specialized prompt mechanism was developed utilizing OpenAI GPT-4.0 and ERNIE Bot-4.0 APIs to assess the urgency of medical attention based on 5,747 simulated patient complaints. A Bidirectional Encoder Representations from Transformers (BERT) machine learning model was employed for text classification to differentiate u

SUBMITTER: Wang MH 

PROVIDER: S-EPMC11865202 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature