Critical Assessment of Large Language Models' (ChatGPT) Performance in Data Extraction for Systematic Reviews: Exploratory Study.

ABSTRACT:

Background

Systematic literature reviews (SLRs) are foundational for synthesizing evidence across diverse fields and are especially important in guiding research and practice in health and biomedical sciences. However, they are labor intensive due to manual data extraction from multiple studies. As large language models (LLMs) gain attention for their potential to automate research tasks and extract basic information, understanding their ability to accurately extract explicit data from academic papers is critical for advancing SLRs.

Objective

Our study aimed to explore the capability of LLMs to extract both explicitly outlined study characteristics and deeper, more contextual information requiring nuanced evaluations, using ChatGPT (GPT-4).

Methods

We screened the ful

SUBMITTER: Mahmoudi H 

PROVIDER: S-EPMC12425462 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature