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Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

Aydin, Zafer; Sieberts, Solveig K.; Schaff, Jennifer; Duda, Marlena; Pataki, Balint Armin; Sun, Ming; Snyder, Phil; Daneault, Jean-Francois; Parisi, Federico; Costante, Gianluca; Rubin, Udi; Banda, Peter; Chae, Yooree; Chaibub Neto, Elias; Dorsey, E. Ray; Chen, Aipeng; Elo, Laura L.; Espino, Carlos; Glaab, Enrico; Goan, Ethan; Golabchi, Fatemeh Noushin; Gormez, Yasin; Jaakkola, Maria K.; Jonnagaddala, Jitendra; Klen, Riku; Li, Dongmei; McDaniel, Christian; Perrin, Dimitri; Perumal, Thanneer M.; Rad, Nastaran Mohammadian; Rainaldi, Erin; Sapienza, Stefano; Schwab, Patrick; Shokhirev, Nikolai; Venalainen, Mikko S.; Vergara-Diaz, Gloria; Zhang, Yuqian; Wang, Yuanjia; Guan, Yuanfang; Brunner, Daniela; Bonato, Paolo; Mangravite, Lara M.; Omberg, Larsson (NATURE RESEARCHHEIDELBERGER PLATZ 3, BERLIN 14197, GERMANY, 2021)

Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex ...