US 12,357,416 B2
Deep-learning-based real-time remaining surgery duration (rsd) estimation
Mona Fathollahi Ghezelghieh, Sunnyvale, CA (US); Jocelyn Elaine Barker, San Jose, CA (US); and Pablo Eduardo Garcia Kilroy, Menlo Park, CA (US)
Assigned to Verb Surgical Inc., Santa Clara, CA (US)
Filed by Verb Surgical Inc., Santa Clara, CA (US)
Filed on Apr. 4, 2024, as Appl. No. 18/408,329.
Application 18/408,329 is a continuation of application No. 17/208,715, filed on Mar. 22, 2021, granted, now 11,883,245.
Prior Publication US 2025/0025259 A1, Jan. 23, 2025
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 90/00 (2016.01); G06N 3/047 (2023.01); G06N 3/08 (2023.01); G16H 10/00 (2018.01)
CPC A61B 90/37 (2016.02) [G06N 3/047 (2023.01); G06N 3/08 (2013.01); G16H 10/00 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for predicting in real-time a remaining surgical duration (RSD) of a live surgical session of a surgical procedure based on a real-time endoscope video of the live surgical session, the method comprising:
sampling a set of N frames of the endoscope video corresponding to the elapsed portion of the live surgical session between a) the beginning of the endoscope video corresponding to the beginning of the live surgical session and b) a current frame corresponding to a current time of the live surgical session;
feeding the set of N frames into a trained RSD machine-learning (ML) model for the surgical procedure;
outputting a current RSD prediction from the trained RSD ML model based on the set of N frames, wherein the outputted current RSD prediction is part of a real-time RSD prediction sequence of the live surgical session; and
predicting a delay based on determining a deviation, as the real-time RSD prediction sequence or a real-time RSD prediction curve deviates from a standard or ideal RSD prediction curve.