Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

BACKGROUND: The COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS). OBJECTIVE: We presented a machine learning approach leveraging passive sensor data from smartphones and fitness trackers of peo...

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Detalles Bibliográficos
Autores principales: Chikersal, Prerna, Venkatesh, Shruthi, Masown, Karman, Walker, Elizabeth, Quraishi, Danyal, Dey, Anind, Goel, Mayank, Xia, Zongqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407162/
https://www.ncbi.nlm.nih.gov/pubmed/35849686
http://dx.doi.org/10.2196/38495

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407162/
https://www.ncbi.nlm.nih.gov/pubmed/35849686
http://dx.doi.org/10.2196/38495

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