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The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our […]

Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require manual, time-consuming, and error-prone calculations that are further hindered by the use of static variable thresholds derived from aggregate patient populations. These coarse frameworks do not capture time-sensitive individual physiological patterns and are not suitable for instantaneous assessment of patients’ […]

Chronic pain, including arthritis, affects about 100 million adults in the United States. Complexity and diversity of pain experience across time and people and its fluctuations across and within days show the need for valid pain reports that do not rely on patient’s long-term recall capability. Smartwatches can be used as digital ecological momentary assessment […]