T-2017-012 Assessing trainee performance on surgical training simulators with Machine Learn

• Unité de recherche: INNOSUISSE
• Numéro de projet: 26134.1 PFSATW-ES
• Titre du projet anglais: T-2017-012 Assessing trainee performance on surgical training simulators with Machine Learn

Description succincte (Allemand)

T-2017-012 Assessing trainee performance on surgical training simulators with Machine Learn

Description succincte (Anglais)

T-2017-012 Assessing trainee performance on surgical training simulators with Machine Learn

Résumé des résultats (Abstract) (Allemand)

Surgical training simulators offer the ability to track every action of the trainee accurately and digitally. Today, the assessment of the surgical skills is derived from collaborations with KOLs or medical societies who define a set of criteria that define the surgical performance. However, selection of the criteria and setting a threshold for good performance are primarily consensus-driven. Simulators can collect best-practice data that can be leveraged for providing optimal training.

Résumé des résultats (Abstract) (Anglais)