Interpretation of intraoperative sensor data using concept graph neural networks

US12362068B2 · kind B2 · utility

Assignees

• The General Hospital Corporation · US
• Massachusetts Institute of Technology · US

Inventors

• Ozanan Meireles · Cambridge, US
• Yutong Ban · Boston, US
• Daniel A. Hashimoto · Boston, US
• Guy Rosman · Newton, US
• Thomas Ward · Boston, US
• Daniela Rus · Weston, US

Key dates

• Filing date: Mar 28, 2022
• Grant date: Jul 15, 2025
• Expiry date: Jul 19, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/08
• WIPO field: Medical technology
• WIPO sector: Instruments

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.