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NHS England - Transformation Directorate
Find guidance to develop your AI. Get inspired by challenges facing individuals and organisations developing AI and how they overcame them.
AI in imaging: resource collection
A collection of resources about the use of medical imaging data in artificial intelligence tools for health and social care.
Algorithmic impact assessment: a case study in healthcare
This Ada Lovelace Institute report sets out the first-known detailed proposal for the use of an algorithmic impact assessment for data access in a healthcare context.
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software
An article exploring the production of realistic synthetic data based on UK primary care patient data. Published in Nature.com, November 2020.
Practical lessons from generating synthetic healthcare data with Bayesian networks
Academic paper from the MHRA and the Intelligent Data Analysis Group at Brunel University.
BayesBoost: Identifying and handling bias using synthetic data generators
External research paper from MHRA and Brunel University exploring attempts to create synthetic data that lead to predictive models with better performance.
Evidence Standards Framework
NICE's Evidence Standards Framework for Digital Health Technologies. It offers support and guidance to developers so they can generate high quality evidence. It is closely aligned to regulatory requirements and is easy to use.
Understand best practice in commissioning AI and get inspired by learning how organisations overcome challenges they faced adopting AI.
Learn about AI and its potential to transform health and care.