Abstract: The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.

Abstract: Techniques are described for improving computer-assisted surgical (CAS) systems, particularly, to recognize surgical phases in a video of a surgical procedure. A CAS system includes cameras that provide video stream of a surgical procedure. According to one or more aspects the surgical phases are automatically detected in the video stream using a machine learning model. Particularly, the machine learning model includes a boundary aware cascade stage network to perform surgical phase recognition.

Abstract: An aspect includes a computer-implemented method that de-identifies data received from microphones. The method includes receiving data from one or more microphones and de-identifying the data. The de-identifying includes inputting the data into a machine learning system that has been trained to detect patterns in the data that are likely to identify a specific entity, and to remove the detected patterns from the data to generate de-identified data. An output from the machine learning system is received, where the output includes the de-identified data. According to some aspects, the microphones can be located in an operating room.

Abstract: A medical instrument includes a housing and a shaft coupled to the housing. The shaft has a proximal end and a distal end. An end effector assembly is disposed at the distal end of the shaft. The end effector assembly includes first and second jaw members. At least one of the first and second jaw members is movable from a first position wherein the first and second jaw members are disposed in spaced relation relative to one another to at least a second position closer to one another wherein the first and second jaw members cooperate to grasp tissue therebetween. The medical instrument also includes one or more light-emitting elements and one or more light-detecting elements configured to generate one or more signals indicative of tissue reflectance. The one or more light-emitting elements are adapted to deliver light energy to tissue grasped between the first and second jaw members.

Abstract: A medical instrument includes a housing and a shaft coupled to the housing. The shaft has a proximal end and a distal end. An end effector assembly is disposed at the distal end of the shaft. The end effector assembly includes first and second jaw members. At least one of the first and second jaw members is movable from a first position wherein the first and second jaw members are disposed in spaced relation relative to one another to at least a second position closer to one another wherein the first and second jaw members cooperate to grasp tissue therebetween. The medical instrument also includes one or more light-emitting elements and one or more light-detecting elements configured to generate one or more signals indicative of tissue reflectance. The one or more light-emitting elements are adapted to deliver light energy to tissue grasped between the first and second jaw members.