John Prince
TitleCited byYear
Big data in Parkinson’s disease: using smartphones to remotely detect longitudinal disease phenotypes
J Prince, S Arora, M de Vos
Physiological measurement 39 (4), 044005, 2018
102018
A Deep Learning Framework for the Remote Detection of Parkinson’s Disease Using Smart-phone Sensor Data
J Prince, M De Vos
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
52018
Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data
J Prince, F Andreotti, M De Vos
IEEE Transactions on Biomedical Engineering 66 (5), 1402-1411, 2018
32018
EARLY ADVERSITY, BRAIN INJURY AND LATER LIFE OUTCOMES: A DEMENTIAS PLATFORM UK INVESTIGATION USING MULTI-COHORTS AND MACHINE LEARNING
J Prince
Alzheimer's & Dementia: The Journal of the Alzheimer's Association 15 (7), P493, 2019
2019
Evaluation of Source-wise Missing Data Techniques for the Prediction of Parkinson’s Disease Using Smartphones
J Prince, F Andreotti, M De Vos
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
2019
Discriminating Progressive Supranuclear Palsy from Parkinson's Disease using wearable technology
M De Vos, J Prince, TI Buchanan, J FitzGerald, CA Antoniades
medRxiv, 19006866, 2019
2019
Mobile Messaging Support Versus Usual Care for People With Type 2 Diabetes on Glycemic Control: Protocol for a Multicenter Randomized Controlled Trial
A Farmer, K Bobrow, N Leon, N Williams, E Phiri, H Namadingo, ...
JMIR research protocols 8 (6), e12377, 2019
2019
Objective Assessment of Parkinson's Disease using Machine Learning
J Prince
University of Oxford, 2018
2018
Evaluation of The Inherent Strain Method for the Determination of Sub-Surface Residual Stress
J Prince
University of Bristol, 2014
2014
Vital-Sign Monitoring Using Pulse Oximetry for Automated Triage and the Prediction of Patient Deterioration
J Prince
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