March 21-23, Stanford University
Automated human health-state monitoring aims to identify when an individual moves from a healthy to a compromised state. For example, changes in diet or physical activity can lead to life-threatening hypo or hyperglycemia in diabetics. Similarly, elderly individuals managing multiple chronic conditions may experience rapid changes in physical and cognitive health state that must be caught quickly for treatments to be most effective. Even in healthy individuals, heavy exertion in extreme climates can quickly lead to life threatening situations.
The emergence of inexpensive and unobtrusive health sensors promises to shift the healthcare industry’s focus from episodic care in acute settings to early detection and longitudinal care for chronic conditions in natural living environments. The same technologies can also be used to monitor healthy individuals in high-stress work situations. While these sensing systems are able to provide a wealth of physiological information, these measurements are often quite different from those used by physicians. The medical community is accustomed to making decisions from high-quality clinical data from a limited set of sessions. Data from continuously measuring sensors requires us to draw conclusions from large quantities of lower quality data from subacute environments where these measures are often not specific to health states of interest and can reflect the output of multiple latent variables. As the availability of longitudinal data increases, we have an unprecedented opportunity to discover new early predictors of clinically significant events.
This symposium will bring together researchers from the fields of artificial intelligence, machine learning, engineering, physiology, and medicine. The symposium will have invited talks and panels by select attendees to share relevant completed work. We will have breakout sessions and poster sessions to foster speculative discussions and presentation of works in progress. The goal of the symposium is to allow ample time for discussion and bridging of interdisciplinary perspectives.
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