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Search found 4 items
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project will apply machine learning against a large data set to develop a model to both understand and predict surgical cancellations on individual pediatric patients at two pediatric surgical sites.
This project informed Stage 3 Meaningful Use requirements by evaluating metrics related to identification of delirium in real time and improving accuracy of the problem list, thus potentially improving care for patients with delirium.
Documented the patient safety and health care quality challenges in critical access to rural hospitals, and assessed health IT capacity in these rural hospitals and how they would use health IT to improve safety and quality; developed decisionmaking health IT toolkits for other rural hospitals.