This month, I presented the Clinical Trial Risk Tool at the Plotly Dash in Action webinar. I was interviewed by Plotly’s Community Manager Adam Schroeder. You can watch the relevant part of the webinar below.
The Clinical Trial Risk Tool was one of four interactive apps presented as part of the webinar. The speakers at the webinar were:
- Matteo Trachsel, Head of Sustainability at Thermoplan AG, Switzerland, who presented his Product Environmental Report Dash App, which calculates the carbon footprint of coffee machine usage.
- Thomas Wood, Data Scientist at Fast Data Science, UK.
- Nadia Blostein, Research Associate at NeuroPoly Lab, Polytechnique Montréal, who presented an MRI image processing app on behalf of Agah Karakuzu, Canada. The dashboard allows researchers to compare datasets from brains and phantoms (calibration devices containing water, used to test MRI machines) from the three main MRI machine vendors (Phillips, GE and Siemens).
- Gabriele Albini, Lead Data Architect at Afiniti, Italy, who presented his sARIMA Tuner.
Screenshot of Matteo Trachsel’s Thermoplan dashboard which calculates the carbon footprint of coffee machine usage.
Screenshot of Agah Karakuzu’s dashboard which allows neuroscientists to assess the reproducibility of T1 values across different sites and vendors where researchers used the same research protocol. (T1 is the time it takes water molecules in the brain to return to their original state following a magnetic pulse).
How to cite 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}
}
