Methodological insights into ChatGPT's screening performance in systematic reviews.

ABSTRACT:

Background

The screening process for systematic reviews and meta-analyses in medical research is a labor-intensive and time-consuming task. While machine learning and deep learning have been applied to facilitate this process, these methods often require training data and user annotation. This study aims to assess the efficacy of ChatGPT, a large language model based on the Generative Pretrained Transformers (GPT) architecture, in automating the screening process for systematic reviews in radiology without the need for training data.

Methods

A prospective simulation study was conducted between May 2nd and 24th, 2023, comparing ChatGPT's performance in screening abstracts against that of general physicians (GPs). A total of 1198 abstracts across three subfields of radiology w

SUBMITTER: Issaiy M 

PROVIDER: S-EPMC10976661 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature