Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort (Preprint)

Benjamin Lam; Michael Catt; Sophie Cassidy; Jaume Bacardit; Philip Darke; Sam Butterfield; Ossama Alshabrawy; Michael Trenell; Paolo Missier

doi:10.2196/preprints.23364

Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort (Preprint)

Benjamin Lam, Michael Catt, Sophie Cassidy, Jaume Bacardit, Philip Darke, Sam Butterfield, Ossama Alshabrawy, Michael Trenell, Paolo Missier

Computer Science

Research output: Working paper/Preprint › Preprint

Original language	English
DOIs	https://doi.org/10.2196/preprints.23364
Publication status	Published - 6 Sept 2020

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.2196/preprints.23364

Cite this

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AU - Missier, Paolo

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