Coordination of Care: Optimized Scheduling Algorithm
ColumbiaDoctors at CUIMC
The project aims to develop a proof-of-concept Deep Learning (DL) model to optimize patient scheduling in an example case. An artificial intelligence or machine learning algorithm will enable schedule optimization to minimize patient time spent in a hospital or testing sites across locations by ensuring that schedules follow pre-determined operational rules. The project will specifically look to automate manual responsibility for patients and schedulers in managing complex initial, subsequent encounters, and diagnostic testing.