Abstract: Systems and methods are provided for generating a statistical parameter representing a state of a surgical procedure from sensor data. Sensor data representing a time period. is received from a sensor. Numerical features representing the time period are generated from the sensor data. Each of a plurality of long short term memory units are updated according to the plurality of numerical features via a message passing process. The long short term memory units are connected to form a graph, with a first set of the long short term memory units representing a plurality of nodes of the graph and a second set of the long short term memory units representing a plurality of hyperedges of the graph. A statistical parameter representing a state of the surgical procedure for the time period is derived from an output of one of the long short term memory units and provided to a user.

Abstract: Systems and methods are provided for identifying a current phase of a surgical procedure. Sensor data representing a time period is received and a plurality of numerical features representing the time period are generated from the sensor data. A statistical parameter representing a plurality of stored values from a memory is generated at a sufficient statistics model. An output, representing a surgical phase associated with the time period is provided at a recurrent neural network from a set of inputs that includes the plurality of numerical features and the statistical parameter.