AI Healthcare Academy - Accelerating the use of quality and trustworthy data

Ensuring the deployment of safe, ethical and trustworthy AI standards, while promoting patient trust, developer certainty and user confidence in the health and life sciences sector..

Quality healthcare data is critical to the development of effective AI in healthcare solutions and applications. Patients are in a key position, not only as generators and recipients of the potential benefits of health-related data science but also in sourcing and providing quality data that helps minimise bias inherent in healthcare data.

Research and recent controversies show that if patients understand the life-saving benefits of the use of their data in healthcare for critical aspects such as drug safety, developing predictive models used for early diagnosis and for examining links between social and behavioural factors and health outcomes, then they are far more likely to support these uses and to provide consent.

Empowering patients clearly requires effective public involvement and engagement in data health research.


Join this session to hear about:

  • NPL’s pioneering work on data quality metrology and assurance, and how to avoid complexity in AI;
  • Recent research findings on current use of health data in Europe
  • Our expert panel’s views on the essentials for rapid progress of safe and trustworthy adoption of AI in health and life sciences.

Who should attend?

Life sciences / healthcare professionals


Event date

14:00 - 16:00 GMT


Arup Paul

Clinical Director at LovedBy

Lara Groves

Researcher at Ada Lovelace Institute

Maya Carlyle

Principal Enterprise Architect at National Physical Laboratory

Sundeep Bhandari

Strategy Manager at National Physical Laboratory