Enabling micro-assessments of skills in the simulated setting using temporal artificial intelligence-models.

Background: Assessing skills in simulated settings is resource-intensive and lacks validated metrics. Advances in AI offer the potential for automated competence assessment, addressing these limitations. This study aimed to develop and validate a machine learning AI model for automated evaluation during simulation-based thyroid ultrasound (US) training.

Validating the virtual: a deep dive into ultrasound simulator metrics in otorhinolaryngology.

Purpose: This study aimed to assess the validity of simulation-based assessment of ultrasound skills for thyroid ultrasound.

Methods: The study collected validity evidence for simulation-based ultrasound assessment of thyroid ultrasound skills. Experts (n = 8) and novices (n = 21) completed a test containing two tasks and four cases on a virtual reality ultrasound simulator (U/S Mentor's Neck Ultrasound Module).