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NPJ Digital Medicine|December 10, 2019
Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patientsAntonin Dauvin, Carolina Donado, Patrik Bachtiger, et al.
NPJ Digital Medicine|February 13, 2020
Investigating sources of inaccuracy in wearable optical heart rate sensorsBrinnae Bent, Benjamin A Goldstein, Warren A Kibbe, et al.
NPJ Digital Medicine|January 24, 2020
What is the clinical value of mHealth for patients?Simon P Rowland, J Edward Fitzgerald, Thomas Holme, et al.
NPJ Digital Medicine|January 24, 2020
mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's diseaseM Kelley Erb, Daniel R Karlin, Bryan K Ho, et al.
NPJ Digital Medicine|November 4, 2020
Feasibility of the deep learning method for estimating the ventilatory threshold with electrocardiography dataKotaro Miura, Shinichi Goto, Yoshinori Katsumata, et al.
NPJ Digital Medicine|November 4, 2020
Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary careRalph K Akyea, Nadeem Qureshi, Joe Kai, et al.
NPJ Digital Medicine|November 4, 2020
A randomised controlled feasibility trial of E-health application supported care vs usual care after exacerbation of COPD: the RESCUE trialMal North, Simon Bourne, Ben Green, et al.
NPJ Digital Medicine|November 2, 2020
Harnessing consumer smartphone and wearable sensors for clinical cancer researchCarissa A Low
NPJ Digital Medicine|September 5, 2020
Deep learning for automated sleep staging using instantaneous heart rateNiranjan Sridhar, Ali Shoeb, Philip Stephens, et al.
NPJ Digital Medicine|September 9, 2020
Predicting risk of late age-related macular degeneration using deep learningYifan Peng, Tiarnan D Keenan, Qingyu Chen, et al.
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