Integrated AI-powered adaptive robotic surgery system

A robotic surgical system network, comprising:

• a plurality of robotic surgical systems for performing one or more surgical procedures;
• a network interface associated with each robotic surgical system, the network interface configured for secure data communication, each robotic surgical system including a surgeon console coupled to a surgeon computer, a patient console, and a sensor array producing a sensor array input, wherein the patient console is coupled to a surgical robot with a plurality of robotic surgical instruments configured to manipulate a target tissue for at least one surgical procedure selected from:
• resection, dissection, ablation, ligation, stapling, biopsy, suturing, and cauterization;
• an imaging system including a sensor array producing a sensor array input with an imaging quality, and one or more cameras configured to acquire baseline pre-operative image data of at least a portion of a surgical site before initiation of tissue modification, including surgical target tissue to be modified or removed and one or more critical structures or tissue boundaries, and real-time intraoperative image data during the surgical procedure, wherein acquisition of the baseline pre-operative image before the surgical procedure allows the surgeon to visualize and create a modifiable surgical plan based on a patient's anatomy;
• a central or distributed data repository coupled to the network interface, the central or distributed data repository configured to securely store surgical data from the one or more surgical procedures;
• a control system coupled to the surgical robot and the plurality of robotic surgical instruments;
• an artificial intelligence (AI) system coupled to the surgical robot, the control system, the sensory array, and the imaging system, the AI system including an AI architecture configured to process spatial and contextual data to generate and update a three dimensional (3D) model of the of the surgical site, analyze the 3D model using machine learning to determine positioning of at least a portion of the plurality of robotic surgical instruments at the surgical site while avoiding one or more critical structures, and issue control signals to actuate positioning of at least a portion of the plurality of robotic surgical instrument at the surgical site, the 3D model being configured to be modified during the surgical procedure, to indicate tissue boundaries at the surgical site, the critical structures being tissues to be protected or avoided;
• and
• the robotic surgical system network being configured to track regulatory requirements for privacy of patient data before, during, and after a surgical procedure.