Date: 3rd November 2017
Venue: Alan Turing Institute, 96 Euston Road, London
The UK Health Data Analytics Network (UK-HDAN) hosted a one-day participatory workshop at the Alan Turing Institute to bring together health informaticians and data science methodologists.
The aim was to explore in depth the methodological challenges posed by health data, building on the UK-HDAN Research Roadmap, a living document, which provides a framework of Healthcare Opportunities and Data Science Challenges. The intention is that, through sharing insights and experience, participants will identify new opportunities for research and collaboration. The meeting will also contribute to further development of the Roadmap.
The workshop discussion sessions addressed a number of topics, focusing on specific areas selected in advance by the attendees.
- Integrating Heterogeneous Data: representation and data models, provenance, robust linkage, using context.
- Dealing with Imperfect Data: heterogeneously sampled data, missing and anomalous data, temporal drift, integrating inference and data cleaning, managing uncertainty.
- Predictive Models: holistic models of individuals, modelling complex temporal behaviour, borrowing strength.
- Identifying Subgroups: robust identification, feature selection and dimensionality reduction, transferability.
ALL BREAKOUT SESSION OUTPUT IS AVAILABLE HERE
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