Promoting the use of R in the NHS

Blog Article

Article originally appeared on What a NHS-R Community Conference it was – simply wow! – Hutsons-hacks and was submitted by Gary Hutson – Senior Data Scientist.

The NHS-R Virtual Conference concluded this week and we have had a number of excellent speakers from the Health & Social Care sector, alongside working with key partners of interest. It kicked off with a full day jammed packed of speakers from all over the NHS. The second day we had international speakers from the US, Australia and other European countries.

The keynotes this year were provided by Professor Frank Harrell who did an excellent talk on “statistical mistakes to avoid” and Julia Silge @RStudio discussing “Preparing and processing text for Machine Learning”. I was lucky enough to chair the afternoon sessions, and it was great welcoming Julia to the stage and running the Q&A.

What if I missed it?

No worries if you missed the days, as we livestreamed it on YouTube for posterity.

Day One – Watch again

There were so many talks to attend on this day and the quality was excellent, here are a few of the talks that stood out for me:

  • 09:30 – Professor Mohammed A Mohammed – NHS-R Conference Opening and Welcome
  • 11:45 – Colin Fay – ThinkR – discussing the role of accessibility in R
  • 14:25 – Sebastien Peytrignet – What can an online shopping algorithm teach us about coordinating outpatient care?
  • I didn’t see all of day one, so this is just a provisional list

Day Two – Watch again

Another stellar day of talks, but here if my selection:

  • 11:10 – Jacob Anhoj – discussing “Run Forest, run! Understanding variation and runs analysis
  • 12:00 – Simon and Chris discussing the new NHSrplotthedots package for statistical process control
  • 12:30 – Simon Moss and Richard Wood – the CCG use of PathSimR to support Covid-19 mass vaccination
  • 15:05 – Frank Harrell – Professor of Biostatistics talking about statistical mistakes to avoid
  • 16:05 – Jeroen Ooms – speaking about the r-universe project

Day Three – watch again

I missed the morning, but I have watched back since and these are my picks, again there is too much content to wade through:

  • 09:30 – Gary Hutson – NHS-R Solutions and package funding process, with code! I also ran a workshop at the event. Watch this space for live recordings being uploaded to the NHS-R YouTube page.
  • 10:05 – Sukhmeet Panesar – connecting the data and analytic workforce and creating a social movement for good: the story of AnalystX
  • 11:05 Hugo Cosh and Zoe Strawbridge – Shiny doesn’t have to be scary. Dicussing flexdashboard and how it is used in Public Health Wales
  • 11:25 – Dr Kate Bamford, Senior Data Surveillance Scientist, East Midlands Health Protection Team UK Health Security Agency Using R Markdown, Reactable and Crosstalk to create an interactive COVID-19 review tool
  • 12:45 – Adam Watkins – mapping public transport travel times – building on and enabling work of others
  • 15:05 – All the lightning talks were fantastic!
  • 16:00 – Julia Silge from RStudio talking about creating features for machine learning from text
  • 17:00 – Close by Chris Beeley – our co-chair of the NHS-R community

Workshops

The NHS-R community also held workshops to support understanding of our packages. These will all be streamed on YouTube and included sessions on Shiny, Tensorflow, TidyModels, NHSDataDictionaRy package, functional programming in R, alongside many others. Please keep an eye out for the NHS-R communities YouTube channel and website.

Thanks and conclusion

Thanks to everyone involved in making the conference a success, and to those out there in the NHS-R community, please make a pledge:

Please pledge @NHSRCommunity on Twitter when you are making your pledge. It is time to say goodbye to the conference. It has been a rollercoaster this year and we will see you all again in 2022, as well as having webinars throughout the year.

Gary Hutson

(Head of Advanced Analytics)

Arden & GEM CSU

My background is in Advanced Analytics and my passions are Machine, Deep Learning, Computer Vision, R, Python, statistics, applied modelling and...

View Author Bio & (11) Posts

Leave a Reply