doi: 10.1145/3292500.3330903 url: https://doi.org/10.1145/3292500.3330903 ISBN: 978-1-4503-6201-6 Year: 2019 Study: mPower Mobile Parkinson Disease Study Title: A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health synID: syn4993293 Author: Neto EC Pratap A Perumal TM Tummalacherla M Bot BM Mangravite L Omberg L Journal: KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining Abstract: syn22017691 Featured: TRUE Diagnosis: Parkinson's disease control Consortium: mHealth sensorType: accelerometer gyroscope magnetometer touchscreen microphone studyOrProject: [mPower Mobile Parkinson Disease Study](/Explore/Studies/DetailsPage?study=mPower%20Mobile%20Parkinson%20Disease%20Study) publicationType: study digitalAssessmentCategory: resting tremor kinetic tremor postural tremor action tremor gait voice