Retrieval augmented scientific claim verification.

ABSTRACT:

Objective

To automate scientific claim verification using PubMed abstracts.

Materials and methods

We developed CliVER, an end-to-end scientific Claim VERification system that leverages retrieval-augmented techniques to automatically retrieve relevant clinical trial abstracts, extract pertinent sentences, and use the PICO framework to support or refute a scientific claim. We also created an ensemble of three state-of-the-art deep learning models to classify rationale of support, refute, and neutral. We then constructed CoVERt, a new COVID VERification dataset comprising 15 PICO-encoded drug claims accompanied by 96 manually selected and labeled clinical trial abstracts that either support or refute each claim. We used CoVERt and SciFa

SUBMITTER: Liu H 

PROVIDER: S-EPMC10919922 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature