DeepOR is a powerful platform to monitor and optimize the use of Hospital Operating Rooms (ORs). It offers advanced features based on Big Data and Computer Vision to help make real-time resource allocation decisions. DeepOR's target is to improve the quality of healthcare delivery and increase financial outcomes for a hospital.
Hospital Operating Rooms are becoming complex and expensive environments.
Yet these assets are underutilized.
Thanks to optical sensors installed inside the OR, the head of operating room can monitor in real time the activity taking place.
DeepOR offers reliable data integration and analytics for rigorous performance measurement.
Our solution uses powerful statistical models to support strategic decision making.
By increasing the effective utilization, waiting-time for patient access to the surgical platform is improved.
Meet the team !
Ilyes co-invented DeepOR's core IP technology. He developed expertise in Image Processing, Computer Vision and Machine Learning with specific applications in the medical field. He holds a Master of Science (MSc) in Computer Science from the University of Houston, a Master in Research from the University of Strasbourg and a Diplôme d'Ingénieur (MEng) from Telecom PS. Ilyes is currently completing his PhD in Computer Science at the University of Houston.
Yasser holds a Master of Science (MSc) in Applied Mathematics from the Ecole Polytechnique and a Diplôme d'Ingénieur (MEng) in Industrial Economics from the Ecole des Mines ParisTech. He previously led several successful projects in the optimal allocation of scarce resources, namely at University of California at Berkeley. Yasser also spent two years as an Innovative Products Developer both in France and the US before cofounding DeepOR.
A jury of experts, investors and entrepreneurs selected DeepOR among over 2000 contestants.
A jury of experts and entrepreneurs selected DeepOR among 147 contestants.
We were offered the opportunity to join the X-UP start-up accelerator.
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