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L2M – Driving Precision in Surgical Robotics Through Dynamic Data Analytics
As the demand for surgical interventions and the complexity of procedures increase, the need for intelligent, scalable solutions for care automation is more urgent than ever. We aim to translate cutting-edge research in neurorehabilitation and functional assessment technologies into a new generation of medical analytics systems. Capable of extracting meaningful insights from surgical procedures, we aim to empower the next generation of medical robotics—supporting greater automation and smarter decision-making in the operating room.
Faculty Supervisor:
Jose Zariffa
Student:
Partner:
DMZ Ventures Inc
Discipline:
Life Sciences
Sector:
Health and Related Sciences & Technology; Artificial Intelligence
University:
University Health Network
Program:
Business Strategy Internship
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