A method of displaying an operational parameter of a surgical system is disclosed. The method includes receiving, by a cloud computing system of the surgical system, first usage data, from a first subset of surgical hubs of the surgical system; receiving, by the cloud computing system, second usage data, from a second subset of surgical hubs of the surgical system; analyzing, by the cloud computing system, the first and the second usage data to correlate the first and the second usage data with surgical outcome data; determining, by the cloud computing system, based on the correlation, a recommended medical resource usage configuration; and displaying, on respective displays on the first and the second subset of surgical hubs, indications of the recommended medical resource usage configuration.

A method of displaying an operational parameter of a surgical system is disclosed. The method includes receiving, by a cloud computing system of the surgical system, first usage data, from a first subset of surgical hubs of the surgical system; receiving, by the cloud computing system, second usage data, from a second subset of surgical hubs of the surgical system; analyzing, by the cloud computing system, the first and the second usage data to correlate the first and the second usage data with surgical outcome data; determining, by the cloud computing system, based on the correlation, a recommended medical resource usage configuration; and displaying, on respective displays on the first and the second subset of surgical hubs, indications of the recommended medical resource usage configuration.

Disclosed is an in-vivo micro-robot for nerve stretching, comprising a channel, and a movable part and a fixed part located at the channel. The movable part is disposed to be movable along the channel, the movable part sleeves the fixed part and is used for driving the fixed part to move along the channel, and the fixed part is connected to a nerve to be stretched. The in-vivo micro-robot is embedded into a patient's body through surgery, so that the extension of the nerve is accelerated and is regular and quantitative, thereby effectively solving the problems of small probability of nerve self-repair and long recovery period in traditional nerve bridging surgery.

Disclosed is an in-vivo micro-robot for nerve stretching, comprising a channel, and a movable part and a fixed part located at the channel. The movable part is disposed to be movable along the channel, the movable part sleeves the fixed part and is used for driving the fixed part to move along the channel, and the fixed part is connected to a nerve to be stretched. The in-vivo micro-robot is embedded into a patient's body through surgery, so that the extension of the nerve is accelerated and is regular and quantitative, thereby effectively solving the problems of small probability of nerve self-repair and long recovery period in traditional nerve bridging surgery.

Provided are computer-implemented methods and systems for generating and/or utilizing data analysis algorithm(s) for predicting and/or detecting a clinical condition related to insertion of a medical instrument toward a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

Provided are computer-implemented methods and systems for generating and/or utilizing data analysis algorithm(s) for predicting and/or detecting a clinical condition related to insertion of a medical instrument toward a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

Embodiments of architecture, systems, and methods to develop a learning/evolving system to robotically perform and model one or more activities of a medical procedure where the medical procedure may include diagnosing a patient's medical condition(s), treating medical condition(s), and robotically diagnosing a patient's medical condition(s) and performing one or more medical procedure activities based on the diagnosis without User intervention where the activities may be performed in computer-based environment formed by the learning/evolving system, live, or a combination thereof.

Embodiments of architecture, systems, and methods to develop a learning/evolving system to robotically perform and model one or more activities of a medical procedure where the medical procedure may include diagnosing a patient's medical condition(s), treating medical condition(s), and robotically diagnosing a patient's medical condition(s) and performing one or more medical procedure activities based on the diagnosis without User intervention where the activities may be performed in computer-based environment formed by the learning/evolving system, live, or a combination thereof.

The following relates generally to systems and methods of trans-esophageal echocardiography (TEE) automation. Some aspects relate to a TEE probe with ultrasonic transducers on a distal end of the TEE probe. In some implementations, if a target is in a field of view (FOV) of the ultrasonic transducers, an electronic beam steering of the probe is adjusted; if the target is at an edge of the FOV, both the electronic beam steering and mechanical joints of the probe are adjusted; and if the target is not in the FOV, only the mechanical joints of the probe are adjusted.

Computer-implemented digital image analysis methods, apparatuses, and systems for robotic installation of surgical implants are disclosed. A disclosed apparatus plans a route within an anatomy of a patient from an incision site to a surgical implant site for robotic installation of a surgical implant. The apparatus uses digital imaging data to identify less-invasive installation paths and determine the dimensions of the surgical implant components being used. The apparatus segments the surgical implant into surgical implant subcomponents and modifies the surgical implant subcomponents, such that they can be inserted using the identified less-invasive installation paths.