Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoT. (arXiv:2211.04509v1 [cs.AI])

Health sensing for chronic disease management creates immense benefits for
social welfare. Existing health sensing studies primarily focus on the
prediction of physical chronic diseases. Depression, a widespread complication
of chronic diseases, is however understudied. We draw on the medical literature
to support depression prediction using motion sensor data. To connect human
expertise in the decision-making, safeguard trust for this high-stake
prediction, and ensure algorithm transparency, we develop an interpretable deep
learning model: Temporal Prototype Network (TempPNet). TempPNet is built …

arxiv diseases interpretable ai iot