Artificial Intelligence in Medicine: Interpreting Clinical Data
Papers from the AAAI Spring Symposium
Isaac Kohane and Serdar Uckun,Cochairs
Many current efforts in artificial intelligence in medicine are geared towards providing decision support for tasks such as monitoring patients' clinical courses, forecasting outcomes, and discovering new relational knowledge. The emphasis of this symposium will be on methodologies that provide robust autonomous performance in data-rich clinical environments ranging from busy outpatient practices to operating rooms and intensive care units. Papers in this report are devoted to methods and research projects which deal with sparse information typical of clinical and outpatient medical practice, and projects dealing with dense information typical of critical care environments.