AI in the OR: COVID Black Box Improves Safety for Patients and Healthcare Providers
Thursday, May 7, 2020
10:00 am – 11:00 am EST
Hosted on Zoom
Speakers: Vanessa Palter, MD, PhD, FRCSC; Scientist, International Centre for Surgical Safety, Li Ka Shing Knowledge Institute, St. Michael’s Hospital; and Director of clinical analytics Surgical Safety Technologies St. Michael’s Hospital
Frank Rudzicz, PhD, Scientist, International Centre for Surgical Safety, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Associate Professor, Department of Computer Science, University of Toronto, Director of AI, Surgical Safety Technologies Inc., Co-Founder, WinterLight Labs Inc., Faculty Member, Vector Institute for Artificial Intelligence; CIFAR Chair in AI
Facilitator: Garth Gibson, President and CEO, Vector Institute
Responding to the current global COVID-19 pandemic, Surgical Safety Technologies (SST) has repurposed its OR Black Box technology to improve safety for patients with COVID-19 and their healthcare providers. OR Black Box records surgical procedures from multiple data sources, including high-definition video cameras and microphones, allowing for deep analysis of technical and non-technical proficiency, performance, and key events leading up to adverse outcomes. With COVID Black Box, SST will deploy a low-cost version of its technology to remotely support healthcare workers working with COVID-19 patients in ICUs and assessment centres across Toronto.
Using a combination of clinical staff and advanced deep learning, SST will use machine learning to analyze:
- Hand hygiene
- Adherence to personal protective equipment (PPE) protocols
- Breaches in safety
- System vulnerability in Ontario
The pilot phase has already begun.
By attending this event participants will:
- Understand how machine learning and clinical considerations can develop together.
- Learn about technology that can be potentially re-used, adapted, and drastically improve safety
- Understand how increasing precision in data can help us make better clinical decisions.
Who should attend:
- Healthcare professionals
- Machine Learning Practitioners
- Government (municipal, provincial, federal)
- Public who have a general interest in learning more about artificial intelligence