We’re proud to announce that the Clinical Trial Risk Tool has been selected as a winner of the Plotly Dash Example Apps Challenge (2023), out of 25 amazing apps submitted by the community!
You can try the tool at clinicaltrialrisk.org.
Natural language processing
Funded by the Bill and Melinda Gates Foundation, this app uses natural language processing, Plotly Dash, and the spaCy and Scikit-Learn libraries to calculate the risk of a clinical trial failing to deliver informative results. It reads the trial protocol and identifies key features from the text which are fed into a risk model.
Thomas Wood will be presenting the tool in a webinar on 7 June 2023 which you can book here.
Thank you to all #PlotlyCommunity members who participated in the recent #Dash Example Apps Challenge, and congratulations to the winning submissions!
— Plotly (@plotlygraphs) May 22, 2023
🥇 Clinical Trial Risk Dash App by Thomas Wood
🥈 SARIMA Tuner by Gabriele Albini
🥉 Product Environmental Report Dash App by…
Meanwhile, an article describing the tool has been published at: Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness. Gates Open Res 2023, 7:56 (https://doi.org/10.12688/gatesopenres.14416.1).
Download the pitch deck for the Clinical Trial Risk Tool
If you would like to cite the tool alone, you can cite:
Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness. Gates Open Res 2023, 7:56 doi: 10.12688/gatesopenres.14416.1.
A BibTeX entry for LaTeX users is
@article{Wood_2023,
doi = {10.12688/gatesopenres.14416.1},
url = {https://doi.org/10.12688%2Fgatesopenres.14416.1},
year = 2023,
month = {apr},
publisher = {F1000 Research Ltd},
volume = {7},
pages = {56},
author = {Thomas A Wood and Douglas McNair},
title = {Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness},
journal = {Gates Open Research}
}
Unleash the potential of your NLP projects with the right talent. Post your job with us and attract candidates who are as passionate about natural language processing.
Hire NLP Experts
How can you predict customer churn using machine learning and AI? In an earlier blog post, I introduced the concept of customer churn. Here, I’d like to dive into customer churn prediction in more detail and show how we can easily and simply use AI to predict customer churn.
A generative AI-based legal advice tool for small businesses in distress We are pleased to announce the publication of our paper A generative AI-based legal advice tool for small businesses in distress, in collaboration with an interdisciplinary team based in the UK and Hungary.
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.
What we can do for you