📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning-Based Cross-sectional Study of the UK Biobank Accelerometer Cohort. (2021)

First Author: Lam B

Attributed to: UK Biobank (core renewal) funded by MRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.2196/23364

PubMed Identifier: 33739298

Publication URI: http://europepmc.org/abstract/MED/33739298

Type: Journal Article/Review

Volume: 6

Parent Publication: JMIR diabetes

Issue: 1

ISSN: 2371-4379