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Tele-Empathy: A Digital Medicine Experiment

Treating chronic health conditions is a drain not only on patients but on healthcare providers. Evidence shows that over time, healthcare providers can get lost in the day-to-day aspects of managing chronic conditions and can begin to lose empathy for the patients suffering from those same conditions. We sought to build the most physiologically accurate simulation device possible with the goal of creating authentic empathy through the recreation of an authentic patient experience.

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Handling Data Gaps in Time Series Using Imputation

Time series forecasts depend on sensors or measurements made in the real, messy world. The sensors flake out, get turned off, disconnect, and otherwise seemingly conspire to cause missing signals. Signals that may tell you what tomorrow's temperature will be or what your blood glucose levels are before bed. We explore methods for handling data gaps and when to consider which.