Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g., wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health,...

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Detalles Bibliográficos
Autores principales: Liu, Jason, Spakowicz, Daniel J., Ash, Garrett I., Hoyd, Rebecca, Ahluwalia, Rohan, Zhang, Andrew, Lou, Shaoke, Lee, Donghoon, Zhang, Jing, Presley, Carolyn, Greene, Ann, Stults-Kolehmainen, Matthew, Nally, Laura M., Baker, Julien S., Fucito, Lisa M., Weinzimer, Stuart A., Papachristos, Andrew V., Gerstein, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412351/
https://www.ncbi.nlm.nih.gov/pubmed/34424894
http://dx.doi.org/10.1371/journal.pcbi.1009303

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412351/
https://www.ncbi.nlm.nih.gov/pubmed/34424894
http://dx.doi.org/10.1371/journal.pcbi.1009303

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