ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.

ABSTRACT:

Background

Influenza in mainland China results in a large number of outpatient and emergency visits related to influenza-like illness (ILI) annually. While deep learning models show promise for improving influenza forecasting, their technical complexity remains a barrier to practical implementation. Large language models, such as ChatGPT, offer the potential to reduce these barriers by supporting automated code generation, debugging, and model optimization.

Objective

This study aimed to evaluate the predictive performance of several deep learning models for ILI positive rates in mainland China and to explore the auxiliary role of ChatGPT-assisted development in facilitating model implementation.

Methods

ILI positivity rate data spanning from 2014 to 2024 were obtained

SUBMITTER: Huang W 

PROVIDER: S-EPMC12227151 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature