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Patient-Generated Health Data Quality for Clinical Use: Human and Technology Factors

Patient-Generated Health Data Quality for Clinical Use: Human and Technology Factors

student.unimelb.edu.auGrayKathleenPhD1BordaAnnPhD1De SouzaRuthPhD11University of MelbourneMelbourneAustraliaCorresponding Author: Robab Abdolkhani rabdolkhani@student.unimelb.edu.auJul-Dec20181709201842e1170326720182982018©Robab Abdolkhani, Kathleen Gray, Ann Borda, Ruth De Souza

Robab Abdolkhani, Kathleen Gray, Ann Borda, Ruth De Souza

iproc 2018;4(2):e11703


Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy

Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy

Souza et al [11] estimated EE during ambulatory activities for a study of 3 patients using a linear formula based on heart rate.MethodsSubjectsThere were 7 subjects with DMD aged 6 to 10 years recruited from the regional neuromuscular clinic at the UC Davis

Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han

JMIR Rehabil Assist Technol 2016;3(2):e7