Welcome to Dr. Daniel Weiand's Public GitHub Repository!
This repository includes presentations I’ve delivered (and the code used to deliver them), including:
- an online workshop on Producing Parameterised Reports using purrr and Quarto; and
- a plenary talk on Predicting Antimicrobial Resistance Rates (AMR) using R and Sharing the Results in the form of Parameterised Reports produced using Quarto.
My name is Dr. Daniel Weiand MBChB FRCPath RCPathME MClinEd and I work as a Consultant Medical Microbiologist at Newcastle upon Tyne Hospitals NHS Foundation Trust.
- I joined Newcastle upon Tyne Hospitals NHS Foundation as a Consultant in 2015, and have special interests in nephrology, urology, solid organ transplantation (kidney and pancreas), vascular surgery, medical education, clinical informatics (#RStats @NHSrCommunity) and quality improvement.
- Before moving to the North East of England, I trained in Aberdeen, Sheffield, York, Hull and Leeds.
- My additional roles and responsibilities include:
- Associate Clinical Lecturer at Newcastle University; and
- Medical Examiner for Newcastle upon Tyne Office; and
- Examiner for the Royal College of Pathologists (RCPath); and
- “Q” fellow at The Health Foundation.
- I am currently enrolled in the 2024/25 PG Cert in Clinical Data Science at Manchester University.
"All models are wrong, but some are useful." - George Box
https://www.newcastlelaboratories.com
https://github.com/send2dan/public/
- NUTH now actively supports the use of R at scale, and it can be installed on any work PC (simply call IT on ext 21000 and ask to be added the “SCCM-R” group)
Background information
- R is one of the most commonly used languages for data science, together with Python.
- Open-source (free) data science programming languages, including R and Python, are used in many industries, including by Dell, Walmart and (increasingly) across the NHS
- Both R and Python benefit from a worldwide community that freely shares peer-reviewed learning and resources, e.g. through GitHub, for anyone to use
- The Goldacre report actively promotes the use of open-source data science programming languages across the NHS. This is with a view to increasing adoption of RAP (Reproducible Analytical Pipelines). The vision is for modern, open-source tools to support better, broader, safer care
- Lord Darzi's report on the state of the National Health Service in England emphasises we are on the precipice of an artificial intelligence (AI) revolution that could transform care for patients.
Resources
- Great resources to learn how to code include:
- NHS-R delivers free-to-NHS-staff online introductory training on R and RStudio/Posit. It’s free to register. These courses are really popular and spaces are limited to about 20 per session. Sessions are scheduled once a month. For further information, please contact: [email protected].
- The NHS-R community also runs the premier data science conference in the NHS, along with regular skill-based webinars.
- Also see NHS-R community blog: https://nhsrcommunity.com/blog/
- There are also many (!) excellent, free textbooks (e.g. R4DS)
- NHS-R supports a thriving Slack community, which is an excellent resource for when you get stuck (most useful if you are able to share a reproducible example of the problem you're encountering)