About the group
The AI and Informatics Special Interest Group (SIG) was established to bring together LabMed members with an interest in artificial intelligence, data science, bioinformatics and statistical analysis/programming. The group provides a forum for sharing knowledge, discussing emerging technologies and supporting the safe and effective use of digital innovation in laboratory medicine.
The group helps to inform relevant LabMed UK strategies and works with organisations including the Royal College of Pathologists and the wider NHS to promote best practice, support learning and contribute to discussions on the implementation and governance of AI in healthcare.
Since its launch in 2024, the group has focused on increasing awareness and understanding of AI within laboratory medicine, exploring regulatory and governance issues, and identifying practical ways to support members. Activities have included reviewing AI standards and guidance, developing introductory resources, signposting educational opportunities, and contributing to national discussions on AI regulation and implementation.
Latest AI resources
External Resources
Please note that these are third party resources and the association cannot endorse their quality.
Software
Reading resources
- National Commission into the Regulation of AI in Healthcare: Recommendations for a future regulatory framework - https://www.gov.uk/government/publications/national-commission-into-the-regulation-of-ai-in-healthcare-recommendations-for-a-future-regulatory-framework
- Using Artificial Intelligence (AI) in health and care professional education: https://www.hcpc-uk.org/education-providers/updates/2026/hcpc-collaborates-on-joint-statement-on-use-of-ai-in-health-and-care-professional-education/
- Tutorial: Hello, Quarto: https://quarto.org/docs/get-started/hello/rstudio.html
- veRification: an R Shiny application for laboratory method verification and validation: https://www.degruyterbrill.com/document/doi/10.1515/cclm-2023-0158/html
- https://www.fharrell.com/post/statml/
- Classification vs. Prediction: https://www.fharrell.com/post/classification/
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Damage Caused by Classification Accuracy and Other Discontinuous Improper Accuracy Scoring Rules: https://www.fharrell.com/post/class-damage/
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In Machine Learning Predictions for Health Care the Confusion Matrix is a Matrix of Confusion: https://www.fharrell.com/post/mlconfusion/
- Statistical Rethinking (foundational): https://xcelab.net/rm/
- Regression Modeling Strategies (intermediate): website and book
- Bayesian Workflow (intermediate): https://avehtari.github.io/Bayesian-Workflow/