Development of Machine Learning Copilot to Assist Novices in Learning Flexible Laryngoscopy.

ABSTRACT:

Objectives

Here we describe the development and pilot testing of the first artificial intelligence (AI) software "copilot" to help train novices to competently perform flexible fiberoptic laryngoscopy (FFL) on a mannikin and improve their uptake of FFL skills.

Methods

Supervised machine learning was used to develop an image classifier model, dubbed the "anatomical region classifier," responsible for predicting the location of camera in the upper aerodigestive tract and an object detection model, dubbed the "anatomical structure detector," responsible for locating and identifying key anatomical structures in images. Training data were collected by performing FFL on an AirSim Combo Bronchi X mannikin (United Kingdom, TruCorp Ltd) using an Ambu aScope 4 RhinoLaryngo Slim connec

SUBMITTER: Miller ME 

PROVIDER: S-EPMC11832335 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature