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AI-enabled clinical research
Practical, sceptical advice on using machine learning and large language models in clinical research: where they add value, how to validate them, and how to document their use for ethics committees and regulators.
Typical questions
- Can AI improve recruitment, phenotyping, adjudication or monitoring in this study, and how would we know?
- What validation, governance and documentation will ethics committees and regulators expect?
- How do we use language models in evidence synthesis and study documentation without compromising integrity?
- Which data, consent and data-residency constraints apply?
What you receive
- 1Use-case assessment with feasibility and risk rating
- 2Validation and documentation plan aligned with reporting guidelines
- 3Working sessions with the study team
Well suited to
Study teams, data-science groups, hospitals and societies developing AI policies.
Advice is scientific and methodological; it is not legal or regulatory counsel.