Ontology highlight
ABSTRACT: Aims
Traditional approaches to designing clinical trials for heart failure (HF) have historically relied on expertise and past practices. However, the evolving landscape of healthcare, marked by the advent of novel data science applications and increased data availability, offers a compelling opportunity to transition towards a data-driven paradigm in trial design. This research aims to evaluate the scope and determinants of disparities between clinical trials and registries by leveraging natural language processing for the analysis of trial eligibility criteria. The findings contribute to the establishment of a robust design framework for guiding future HF trials.Methods and results
Interventional phase III trials registered for HF on ClinicalTrials.gov as of the end of 20
SUBMITTER: Lim YMF
PROVIDER: S-EPMC11631231 | biostudies-literature | 2024 Dec
REPOSITORIES: biostudies-literature