A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation.

ABSTRACT:

Background

A barrier to practicing evidence-based medicine is the rapidly increasing body of biomedical literature. Use of method terms to limit the search can help reduce the burden of screening articles for clinical relevance; however, such terms are limited by their partial dependence on indexing terms and usually produce low precision, especially when high sensitivity is required. Machine learning has been applied to the identification of high-quality literature with the potential to achieve high precision without sacrificing sensitivity. The use of artificial intelligence has shown promise to improve the efficiency of identifying sound evidence.

Objective

The primary objective of this research is to derive and validate deep learning machine models using iterations of Bi

SUBMITTER: Abdelkader W 

PROVIDER: S-EPMC8669577 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature