Robotic arthroscopic surgery with machine learning

A system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the system to perform a process for performing an arthroscopic surgical procedure on a joint using a robotic surgical system, the process comprising:
• acquiring patient data of a patient;
• analyzing, using at least one machine learning algorithm, the patient data to determine one or more ligament-attachment joint stabilization steps for the joint, wherein the at least one machine learning algorithm is trained using prior patient data with favorable outcomes;
• receiving user input regarding the one or more ligament-attachment joint stabilization steps;
• generating a pre-operative score for the one or more ligament-attachment joint stabilization steps based on one or more correlations of the patient data to prior patient data;
• in response to the pre-operative score being above a threshold, generating a robotic-enabled surgical plan for the joint based on user input and the one or more ligament-attachment joint stabilization steps, wherein the robotic-enabled surgical plan includes a sequence of surgical steps with corresponding surgical tools for arthroscopically attaching one or more connectors to at least one ligament of the joint and another structure of the patient to promote stabilization of the joint;
• and
• controlling one or more robotic arms of surgical robot according to the robotic-enabled surgical plan to robotically perform the sequence of surgical steps on the patient.

A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for performing an arthroscopic surgical procedure on a joint using a robotic surgical system, the operations comprising:

• acquiring patient data of a patient;
• analyzing, using at least one machine learning algorithm, the patient data to determine one or more ligament-attachment joint stabilization steps for the joint, wherein the at least one machine learning algorithm is trained using prior patient data with favorable outcomes;
• receiving user input regarding the one or more ligament-attachment joint stabilization steps;
• generating a pre-operative score for the one or more ligament-attachment joint stabilization steps based on one or more correlations of the patient data to prior patient data;
• in response to the pre-operative score being above a threshold, generating a robotic-enabled surgical plan for the joint based on user input and the one or more ligament-attachment joint stabilization steps, wherein the robotic-enabled surgical plan includes a sequence of surgical steps with corresponding surgical tools for arthroscopically attaching one or more connectors to at least one ligament of the joint and another structure of the patient to promote stabilization of the joint;
• and
• controlling one or more robotic arms of surgical robot according to the robotic-enabled surgical plan to robotically perform the sequence of surgical steps on the patient.