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Improving outcomes in surgery with machine learning

Photo of Dr. Matthew Holden

Dr. Matthew Holden

Assistant Professor, School of Computer Science, Carleton University

January 24, 2023 14:30 - 15:30

Azrieli Theatre 302. In-person only (no video streaming or recording), Carleton University




When a patient undergoes surgery, the operating room contains many devices to help perform and monitor the operation. For example, medical imaging devices allow us to see the patient’s anatomy, surgical navigation technology allows us to track the motion of surgical tools, and vital signs monitors allow us to observe the patient’s status. Together, these devices allow the surgeon to successfully perform the surgery. But these devices also produce a lot of data. I will talk about how to analyze this data and use machine learning to help surgeons better perform surgery.


Matthew Holden is an Assistant Professor in the School of Computer Science at Carleton University. Previously, he was a postdoctoral fellow at the Malone Center for Engineering in Healthcare at Johns Hopkins University (Baltimore, USA). He completed his PhD (2018) and MSc (2014) in Computing at Queen's University (Kingston, Canada); he received his BScH (2012) in Applied Mathematics and Physics from Western University (London, Canada). His primary research interest is in surgical data science, where he investigates machine learning methods for time series data collected in the operating environment, with the goal of improving patient outcomes.

Last updated January 17, 2023

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