A method to determine the reliability of a robotic surgical system for producing good clinical outcomes is described herein. The method utilizes machine learning (ML) or artificial intelligence (AI) to classify, analyze, or rank how reliable a robotic system is at producing good clinical outcomes as a function of patient specific factors, medical staff factors, robotic system factors, and/or intraoperative factors. A plurality of potential inputs for the ML or AI algorithms is provided as well as the possible outputs for a given robotic system. The method may be particularly useful for surgical robot manufacturers, surgeons, and health care facilities.
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THINK Surgical, Inc., "Determining the Reliability of a Robotic Surgical System for Producing Good Clinical Outcomes", Technical Disclosure Commons, (May 01, 2020)