A new online course developed by LabMed’s AI and Informatics Special Interest Group
About the programme
Laboratory medicine is changing. Data are more abundant and artificial intelligence/machine learning (AI/ML) tools are increasingly present in clinical workflows, yet many laboratory scientists have had little formal exposure to informatics, data analysis or the principles behind the AI/ML systems shaping their field.
AI and Informatics in Laboratory Medicine is a practical learning programme introducing clinical scientists and medics working in laboratory medicine to the essentials of healthcare informatics, hands-on data analysis, and the responsible use of AI/ML. The course brings together expert speakers from the NHS, industry, and academia to build knowledge progressively across four taught modules supported by a dedicated online R programming course.
The programme is designed for laboratory professionals at all career stages who want to develop their confidence with data and digital tools or explore informatics as a career pathway.
What you will learn
By the end of the programme, participants will be able to:
- describe the informatics landscape in laboratory medicine and the career opportunities within it
- extract, visualise and analyse laboratory datasets using R
- communicate clinical information effectively in a digitally-enabled environment
- critically evaluate AI and machine learning models for use in healthcare, understanding both their potential and their risks.
Course Outline
R 101 (Self-guided online, August–October 2026)
Before the taught programme begins, all participants complete an online R course. This ensures a shared baseline in R programming, covering data import and manipulation, graphing, enzyme kinetics analysis, and data visualisation. Delivered by the Biochemical Society this course is applicable to all specialism. Moderated support is available.
Module 1: Skills and Career Paths in Informatics (Wednesday 16 September 2026, online)
An introduction to the informatics landscape in laboratory medicine and beyond. Expert speakers explore the roles, skills, and career pathways available to laboratory scientists with an interest in data and digital systems.
Module 2: Extracting and Analysing Data (Wednesday 21 October 2026, online)
A practical, hands-on session using R to work with laboratory datasets. Participants will apply data cleaning and transformation techniques, perform method comparison analyses, and produce reproducible analytical outputs guided by experienced clinical scientists and data specialists.
Module 3: Clinical Communication (Wednesday 11 November 2026, online)
This module focuses on how laboratory information is communicated in a modern, digitally-connected healthcare system. Topics include IT and terminology standards, data visualisation for clinical use, and the challenges and opportunities of communicating results in an era of patient empowerment and digital access.
Module 4: Responsible and Safe Use of AI and Machine Learning (Wednesday 9 December 2026, online)
A critical and practical introduction to AI and statistical learning in laboratory medicine. Participants will build and evaluate a simple predictive model in R, explore the differences between AI, machine learning, and statistical modelling, and examine the ethical, governance, and safety considerations that must underpin any AI deployment in healthcare.
Delivery and access
All taught modules are delivered live online with interactive breakout discussions and expert moderation. Supporting materials and a discussion forum are available through the LabMed Learning Academy throughout the programme.
The first cohort is limited to 30 participants.
Who should attend?
This programme is suitable for clinical scientists, biomedical scientists, and laboratory medicine professionals at any career stage, whether you are new to informatics and looking to build foundational skills, or an experienced practitioner seeking to formalise your knowledge and explore new career directions.