Machine learning and the COVID Black Box: Safe monitoring of COVID-19 ICU beds, assessment centres, and surgeries

The project aims to optimize healthcare provider and patient safety and monitor PPE use, to optimize resource utilization during the COVID-19 pandemic. Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these […]

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Cloud platform for machine learning

Surgical Safety Technologies aims to provide healthcare professionals with the opportunity to perform research in areas of surgical performance and education and implement evidence-based solutions to improve patient safety. Search on video content would an ideal functionality to assist with healthcare professionals’ research. This project uses computer vision model to rank the relevance of the […]

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Automated Detection and Classification of Adverse Events in Surgery

During surgeries, it is important to keep track of what is happening with the patient, the steps being taken during the surgery by the operating staff, and unforeseen events that occur. All the previous correspond to the surgical workflow. Keeping track of the workflow is essential to achieving a better and safer surgery. In the […]

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Interoperative Performance Measurement of Surgeons using Deep Learning

Surgery is undoubtedly one of the most important events in a person’s life. It is thus imperative that a feedback system is in place to ensure that proper care is provided to patients during surgery. Currently, such systems involve experienced surgeons watching hours of surgery to determine how well the surgery was performed based on […]

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Operating Room Traffic Assessment: A Video Analysis Approach

Surgical Safety Technology aims to improve operating room safety by capturing and analyzing operation videos. Usually, operating room traffic (like people displacement) has a huge impact on surgery. Unnecessary movements can cause distraction of surgeons and pollution of the sterile environment. This project applies computer vision models to detect and track people movements in the […]

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Intra-operative Error Detection on Surgical Video based on Computer Vision Analysis

The intra-operative errors that occurs in adverse events have been a major concern in healthcare and surgical industry. Conventionally, error-event assessment is done by peer surgeon review, which is time consuming and costly. With the advances in machine learning and computer vision techniques, it is possible to keep track of the operation surgical procedures based […]

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Extending artificial intelligence in the operating room

Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. However, those detections should be interpretable, […]

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