Abstract
Given the ability to extract physiological and behavioral markers from continuous streams of sensor data, a key challenge is to convert the resulting marker sequences into predictions of risk for adverse outcomes, that can be used to inform interventions. The four articles in this part cover visualization, models for temporal data, and a case study on predicting high-stress events.
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Rehg, J.M., Murphy, S.A., Kumar, S. (2017). Introduction to Part III: Markers to mHealth Predictors. In: Rehg, J., Murphy, S., Kumar, S. (eds) Mobile Health. Springer, Cham. https://doi.org/10.1007/978-3-319-51394-2_17
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DOI: https://doi.org/10.1007/978-3-319-51394-2_17
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-51394-2
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