The two open source communities, NHS-R Community and NHS.pycom, are hosting an in-person and virtually streamed annual conference we’ve called RPySOC (incorporating R, Py from Python and using the initials for Open Source Conference). We will have over 120 people in person with as many as double or triple that online. Both in person and virtual attendees are invited to post Q&As and have discussions with peers in our NHS-R Community Slack and which is available throughout the year for technical support, sharing useful information and connecting with others in our profession.
We have R and Python talks throughout two days in lightning (10 minutes) and plenary (20 minutes) slots and we will also have an in person event called an unconference, introduced to us through colleagues at The University of Edinburgh, which runs alongside the talks. This is where attendees put forward suggestions for discussion which others sign up to.
Talks will be recorded and shared on YouTube and slides made available in our conference-2024 repo.
Tickets
In-person attendance - full, but please email us at nhs.rcommunity@nhs.net to join the waiting list.
Virtual attendance - tickets are available by completing this form.
Slack
We will be using a dedicated conference channel #in-person-conference-talks on Slack to take questions for our speakers. Last year this allowed both in-person and virtual attendees to ask questions and inspired discussions that lasted beyond the conference.
There will also be an unconference channel: #unconferencing-session.
A link to join the NHS-R community Slack channel can be found in our postcard. More details on how we use Slack can be found in the NHS-R Way.
fixed_points<-c("Break","Lunch","Registration and coffee","Welcome and Housekeeping","Closing of day")tibble::tribble(~Time, ~Title, ~Speaker,"09:00 – 09:45", "Registration and coffee", "","09:45 – 09:55", "Welcome and Housekeeping", "Zoë Turner","09:55 – 10:20", "RAPping my head against a databricks wall", "Louise Schreuders","10:20 – 10:35", "Reducing mental health inequalities among the BAME residents of Herefordshire and Worcestershire communities", "Oluwatimilehin Olabamiyo","10:35 – 11:00", "Simplifying development of AI applications integrated in EHRs with Health Chain", "Jennifer Jiang-Kells","11:00 – 11:15", "Beyond the dashboard: R for value added insights", "Nicola Farthing","11:15 – 11:45", "Break", "","11:45 – 12:00", "Reimagining NHS dashboards: an open-source approach with plotly-dash", "Jennifer Struthers","12:00 – 12:25", "Using Machine Learning and secondary care activity data to identify risk of cancer earlier", "Scarlett Kynoch","12:25 – 12:40", "The patient does not exist – generating synthetic patient data with Wasserstein GAN", "Simon Newey","12:40 – 13:05", "Streamlining machine learning development at the NHS via open-source tools", "Elias Altrabsheh and James Sibbit","13:05 – 13:07", "rainbowR", "Ella Kaye","13:07 – 13:55", "Lunch", "","13:55 – 14:10","What insights did Glasgow Scottish Ambulance Service (SAS) gain from combining multiple data sources about all chest pain patients from 2023? We'll present about the process and findings of a 1-year long MSc dissertation project.", "Katalin Koszegi","14:10 – 14:25","Predictive Modelling for health and social care capacity planning using open data", "Sebastian Fox","14:25 – 14:50", "To explain or predict: how different modelling objectives change how you use the same tools", "Chris Mainey","14:50 – 15:05", "Using Openxlsx2 to automate excel publications", "Ruth Keane","15:05 – 15:35", "Break", "","15:35 – 15:50", "What I learnt about (programming) languages by building bilingual websites", "Rosemary Walmsley","15:50 – 16:15", "Leveraging R to implement novel theoretical development in online ‘digital twin' simulation modelling", "Richard Wood","16:15 – 16:30", "Should I use your package", "Colin Gillespie","16:30 – 16:45", "Cracking open the TiN: how we build a one-stop statistics website using R, GitHub and BigQuery", "Mohan Del","16:45 – 17:10", "Closing of day", "")|>gt::gt()|>gt::cols_width(Time~px(110),Title~px(500),Speaker~px(150))|>gtExtras::gt_highlight_rows(rows =Title%in%fixed_points)
Time
Title
Speaker
09:00 – 09:45
Registration and coffee
09:45 – 09:55
Welcome and Housekeeping
Zoë Turner
09:55 – 10:20
RAPping my head against a databricks wall
Louise Schreuders
10:20 – 10:35
Reducing mental health inequalities among the BAME residents of Herefordshire and Worcestershire communities
Oluwatimilehin Olabamiyo
10:35 – 11:00
Simplifying development of AI applications integrated in EHRs with Health Chain
Jennifer Jiang-Kells
11:00 – 11:15
Beyond the dashboard: R for value added insights
Nicola Farthing
11:15 – 11:45
Break
11:45 – 12:00
Reimagining NHS dashboards: an open-source approach with plotly-dash
Jennifer Struthers
12:00 – 12:25
Using Machine Learning and secondary care activity data to identify risk of cancer earlier
Scarlett Kynoch
12:25 – 12:40
The patient does not exist – generating synthetic patient data with Wasserstein GAN
Simon Newey
12:40 – 13:05
Streamlining machine learning development at the NHS via open-source tools
Elias Altrabsheh and James Sibbit
13:05 – 13:07
rainbowR
Ella Kaye
13:07 – 13:55
Lunch
13:55 – 14:10
What insights did Glasgow Scottish Ambulance Service (SAS) gain from combining multiple data sources about all chest pain patients from 2023? We'll present about the process and findings of a 1-year long MSc dissertation project.
Katalin Koszegi
14:10 – 14:25
Predictive Modelling for health and social care capacity planning using open data
Sebastian Fox
14:25 – 14:50
To explain or predict: how different modelling objectives change how you use the same tools
Chris Mainey
14:50 – 15:05
Using Openxlsx2 to automate excel publications
Ruth Keane
15:05 – 15:35
Break
15:35 – 15:50
What I learnt about (programming) languages by building bilingual websites
Rosemary Walmsley
15:50 – 16:15
Leveraging R to implement novel theoretical development in online ‘digital twin' simulation modelling
Richard Wood
16:15 – 16:30
Should I use your package
Colin Gillespie
16:30 – 16:45
Cracking open the TiN: how we build a one-stop statistics website using R, GitHub and BigQuery
Mohan Del
16:45 – 17:10
Closing of day
Code
tibble::tribble(~Time, ~Title, ~Speaker,"09:00 – 09:45", "Registration and coffee", "","09:45 – 09:55", "Welcome and Housekeeping", "Zoë Turner","09:55 – 10:20", "The Reusability Crisis in Healthcare Analytics", "Rhian Davies","10:20 – 10:35", "Shift staffing via task load prediction", "Marcos Fabietti","10:35 – 10:50", "Unleashing the power of pathway simulation", "Sammi Rosser","10:50 – 11:15", "Break", "","11:15 – 11:40", "New generic tests for cancer – with R is a clinical scientists best friend", "Joe Shaw","11:40 – 11:55", "Beyond automation: a shiny app to maximise analytical impact routine reporting narrative", "Laura Birks","11:55 – 12:10", "Sharpening my Python skills through self-development of web scraping bank complaints data", "Kenneth Quan","12:10 – 12:25", "GitHub as a team sport", "Matt Dray","12:25 – 13:10", "Lunch", "","13:10 – 13:25", "Presenting fingertips in data in a more friendly format", "Rachel Brown","13:25 – 13:50", "A method to apply temporal graph analysis on electronic patient record data to explore healthcare professional patient interaction intensity", "John Booth","13:50 – 14:05", "Deploying a Shiny app with Docker in a Raspberry Pi", "Pablo León Ródenas","14:05 – 14:20", "Estimating flexible hazard rates for C diff recurrence from electronic health records using the SplinHazard Regression package and other methods in R", "Elisabeth Dietz","14:20 – 14:45", "Assessment of patient feedback using Natural Language Processing (NLP) and textual data analysis in R", "Ana Singh","14:45 – 15:15", "Break", "","15:15 – 15:40", "Forged in the fire: agile project management lessons from the frontline", "Chris Beeley","15:40 – 15:55", "Community Talk – Turing Way", "Sophia Batchelor","15:55 – 16:05", "Community Talk -NHS.Pycom", "Alex Cheung","16:05 – 16:15", "Closing talk NHS-R Community and raffle", "Zoë Turner","16:15 – 16:20", "Raffle", "","16:20", "Closing of the day", "")|>gt::gt()|>gt::cols_width(Time~px(110),Title~px(500),Speaker~px(150))|>gtExtras::gt_highlight_rows(rows =Title%in%fixed_points)
Time
Title
Speaker
09:00 – 09:45
Registration and coffee
09:45 – 09:55
Welcome and Housekeeping
Zoë Turner
09:55 – 10:20
The Reusability Crisis in Healthcare Analytics
Rhian Davies
10:20 – 10:35
Shift staffing via task load prediction
Marcos Fabietti
10:35 – 10:50
Unleashing the power of pathway simulation
Sammi Rosser
10:50 – 11:15
Break
11:15 – 11:40
New generic tests for cancer – with R is a clinical scientists best friend
Joe Shaw
11:40 – 11:55
Beyond automation: a shiny app to maximise analytical impact routine reporting narrative
Laura Birks
11:55 – 12:10
Sharpening my Python skills through self-development of web scraping bank complaints data
Kenneth Quan
12:10 – 12:25
GitHub as a team sport
Matt Dray
12:25 – 13:10
Lunch
13:10 – 13:25
Presenting fingertips in data in a more friendly format
Rachel Brown
13:25 – 13:50
A method to apply temporal graph analysis on electronic patient record data to explore healthcare professional patient interaction intensity
John Booth
13:50 – 14:05
Deploying a Shiny app with Docker in a Raspberry Pi
Pablo León Ródenas
14:05 – 14:20
Estimating flexible hazard rates for C diff recurrence from electronic health records using the SplinHazard Regression package and other methods in R
Elisabeth Dietz
14:20 – 14:45
Assessment of patient feedback using Natural Language Processing (NLP) and textual data analysis in R
Ana Singh
14:45 – 15:15
Break
15:15 – 15:40
Forged in the fire: agile project management lessons from the frontline
Chris Beeley
15:40 – 15:55
Community Talk – Turing Way
Sophia Batchelor
15:55 – 16:05
Community Talk -NHS.Pycom
Alex Cheung
16:05 – 16:15
Closing talk NHS-R Community and raffle
Zoë Turner
16:15 – 16:20
Raffle
16:20
Closing of the day
The unconference was a popular addition to the conference last year. People came forward with ideas and questions inspiring some great discussions on topics ranging from Quarto to statistical tests to NHS-R Community branding. We will be trying out unconferencing again and look forward to seeing you there.
Day one - we will take suggestions for informal group discussions which people can vote for or say they can turn up to.
Day two - we will split the room so that people can move between the speaker sessions and the unconference.
For more information on unconferencing we have a podcast talk with Pawel Orzechowski from the University of Edinburgh who introduced the idea of unconferencing to us and a blog by Ben Murch on how it went at the 2023 conference.
RPySOC24 Unconference sessions:
Code
tibble::tribble(~Time, ~Title,"09:55", "NLP techniques and practical usage questions/discussions ","09:55", "CPD from entry-level to C10 – whats worth doing questions/discussions","10:20", "RAP chat","10:20", "Analytical bugbears - what makes you go grrr!","11:15", "I know R, should I learn Python? I know Python, should I learn R?","11:15", "Structuring a BI Team to allow different skillsets to flourish","11:15", "Data literacy in relation to linked data sets (Sudlow review): who needs it? And where do we start?","11:15", "Data scientists vs data analysts: are we different?","11:40", "Deploying streamlit/shiny/plotly dash apps securely","11:40", "How do we balance using cool AI tools with our environmental responsibilities","13:10", "Do everything in github","13:10", "Writing tests into my code – tips please!","13:50", "Methods in github sustainability","13:50", "Practically introducing R training within our organisation","13:50", "How can we better use data to annual plan in an acute hospital","14:20", "Quarto reporting","14:20", "How to convince managers that we need data science","14:20", "System dynamics simulation",)|>gt::gt()|>gt::cols_width(Time~px(110),Title~px(500),)
Time
Title
09:55
NLP techniques and practical usage questions/discussions
09:55
CPD from entry-level to C10 – whats worth doing questions/discussions
10:20
RAP chat
10:20
Analytical bugbears - what makes you go grrr!
11:15
I know R, should I learn Python? I know Python, should I learn R?
11:15
Structuring a BI Team to allow different skillsets to flourish
11:15
Data literacy in relation to linked data sets (Sudlow review): who needs it? And where do we start?
11:15
Data scientists vs data analysts: are we different?
