Bayesian Structural Time Series for Biomedical Sensor Data: A Flexible Modeling Framework for Evaluating Interventions
Jason J. Liu, Daniel J. Spakowicz, Garrett I. Ash, Rebecca Hoyd, Rohan Ahluwalia, Andrew Zhang, Shaoke Lou, Donghoon Lee, Jing Zhang, Carolyn Jean Presley, Ann T. Greene, Matthew Stults‐Kolehmainen, Laura Marie Nally, Julien S. Baker, Lisa M. Fucito, , Mark Gerstein
This paper applies Bayesian structural time series to biomedical sensor data to evaluate interventions, showing its effectiveness in assessing treatment impacts with complex covariates.
PLoS Computational Biology · Aug 23, 2021Peer-reviewedBioinformatics