Using AI to clear elective surgery backlog during COVID-19 pandemic

AI models can optimize health-care delivery to help offset the backlog of elective surgeries caused by COVID-19. AI models can optimize health-care delivery to help offset the backlog of elective surgeries caused by COVID-19.

Using AI to clear elective surgery backlog during COVID-19 pandemic

In a new study led by University of Waterloo student Natasha Rozario, machine learning was used to create customized models to optimize the efficiency of operating room (OR) booking times. The model enables a 40 per cent increase in the frequency of ORs running on time.

Rozario was inspired to undertake the study after the COVID-19 pandemic resulted in the declaration of an emergency leading to the cessation of elective surgery in Ontario. It is estimated that between March 15 and June 13, there was a provincial backlog of 148,364 surgeries....

https://uwaterloo.ca/stories/news/using-ai-clear-elective-surgery-backlog-during-covid-19