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

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 data into so-called digital biomarkers requires complicated analytical approach...

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Detalles Bibliográficos
Autores principales: Sieberts, Solveig K., Schaff, Jennifer, Duda, Marlena, Pataki, Bálint Ármin, Sun, Ming, Snyder, Phil, Daneault, Jean-Francois, Parisi, Federico, Costante, Gianluca, Rubin, Udi, Banda, Peter, Chae, Yooree, Chaibub Neto, Elias, Dorsey, E. Ray, Aydın, Zafer, Chen, Aipeng, Elo, Laura L., Espino, Carlos, Glaab, Enrico, Goan, Ethan, Golabchi, Fatemeh Noushin, Görmez, Yasin, Jaakkola, Maria K., Jonnagaddala, Jitendra, Klén, Riku, Li, Dongmei, McDaniel, Christian, Perrin, Dimitri, Perumal, Thanneer M., Rad, Nastaran Mohammadian, Rainaldi, Erin, Sapienza, Stefano, Schwab, Patrick, Shokhirev, Nikolai, Venäläinen, Mikko S., Vergara-Diaz, Gloria, Zhang, Yuqian, Wang, Yuanjia, Guan, Yuanfang, Brunner, Daniela, Bonato, Paolo, Mangravite, Lara M., Omberg, Larsson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7979931/
https://www.ncbi.nlm.nih.gov/pubmed/33742069
http://dx.doi.org/10.1038/s41746-021-00414-7

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