
Clinical trials are the backbone of medical progress, but a worrying trend is emerging: a large portion end without delivering useful results. This “uninformativeness” wastes valuable resources and delays advancements.
Fast Data Science is excited to announce the publication of a technical research paper the Clinical Trial Risk Tool, a game-changer in identifying potential uninformativeness at the protocol stage!
The Clinical Trial Risk Tool is a browser-based tool which uses Natural Language Processing (NLP) to analyse clinical trial protocols. Here’s how it works:
Ready to fight uninformativeness? Head over to https://clinicaltrialrisk.org/tool and access this free, open-source software.
A BibTex citation is as follows:
@article{wood2023clinical,
title={Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness},
author={Wood, Thomas A and McNair, Douglas},
journal={Gates Open Research},
volume={7},
number={56},
pages={56},
year={2023},
publisher={F1000 Research Limited}
}
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Thomas Wood presents the Clinical Trial Risk Tool before the November meeting of the Clinical AI Interest Group at Alan Turing Institute The Clinical AI Interest group is a community of health professionals from a broad range of backgrounds with an interest in Clinical AI, organised by the Alan Turing Institute.

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