Using wearable activity trackers to predict Type-2 Diabetes: A machine learning-based cross-sectional study of the UK Biobank accelerometer cohort. Lam, B, Catt, M, Cassidy, S, Bacardit, J, Darke, P, Butterfield, S, Alshabrawy, O, Trenell, M, & Missier, P JMIR Diabetes, January, 2021. Paper doi bibtex 2 downloads @article{lam_using_2021,
title = {Using wearable activity trackers to predict {Type}-2 {Diabetes}: {A} machine learning-based cross-sectional study of the {UK} {Biobank} accelerometer cohort},
url = {https://preprints.jmir.org/preprint/23364},
doi = {10.2196/23364},
journal = {JMIR Diabetes},
author = {Lam, B and Catt, M and Cassidy, S and Bacardit, J and Darke, P and Butterfield, S and Alshabrawy, O and Trenell, M and Missier, P},
month = jan,
year = {2021},
}
Downloads: 2
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