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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,...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
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 |
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