Artificial intelligence for automatic and objective assessment of competencies in flexible bronchoscopy.

ABSTRACT:

Background

Bronchoscopy is a challenging technical procedure, and assessment of competence currently relies on expert raters. Human rating is time consuming and prone to rater bias. The aim of this study was to evaluate if a bronchial segment identification system based on artificial intelligence (AI) could automatically, instantly, and objectively assess competencies in flexible bronchoscopy in a valid way.

Methods

Participants were recruited at the Clinical Skills Zone of the European Respiratory Society Annual Conference in Milan, 9^th-13^th September 2023. The participants performed one full diagnostic bronchoscopy in a simulated setting and were rated immediately by the AI according to its four outcome measures: diagnostic completeness (DC), structur

SUBMITTER: Cold KM 

PROVIDER: S-EPMC11494585 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature