Background This study used natural language processing (NLP) and machine learning (ML)
techniques to identify reliable patterns from within research narrative documents to …

Clinical trials that terminate prematurely without reaching conclusions raise financial, ethical,
and scientific concerns. Scientific studies in all disciplines are initiated with extensive …

Background: Evidence-based clinical practice relies on unbiased reporting of negative
results. Meta-analysis of drug safety and efficacy across many clinical trials is difficult given …

In this study, we propose to use machine learning to understand terminated clinical trials.
Our goal is to answer two fundamental questions:(1) what are common factors/markers …

This study proposes using a machine learning pipeline to optimise clinical trial design. The
goal is to predict early termination probability of clinical trials using machine learning …

Background Clinical trials that end prematurely (or “terminate”) raise financial, ethical, and
scientific concerns. The extent to which the results of such trials are disseminated and the …

Abstract Background and Objective When a randomized clinical trial (RCT) prematurely
discontinues, it is essential that stakeholders do the right thing to ensure that lessons can be …

Methods| We identified all interventional clinical trials enrolling adults with at least 1 trial site
in the US; with any trial status listed; investigating a drug, biological product, or device; and …

Abstract The FDA Amendments Act (FDAAA) required that information for certain clinical
trials, such as details about study design features and endpoints, as well as results, be …

Background One quarter of randomized clinical trials (RCTs) are prematurely discontinued
and frequently remain unpublished. Trial registries can document whether a trial is ongoing …