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Safe AI for health and beyond -- Monitoring to transform a health service
Machine learning techniques are effective for building predictive models because they identify patterns in large datasets.
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data
Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing.
An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System
One of the Greater London Authority's (GLA) response to the COVID-19 pandemic brings together multiple large-scale and heterogeneous datasets capturing mobility, transportation and traffic activity over the city of London to better understand 'busyness' and enable targeted interventions and effective policy-making.
Near Real-Time Social Distance Estimation in London
During the COVID-19 pandemic, policy makers at the Greater London Authority, the regional governance body of London, UK, are reliant upon prompt and accurate data sources.
