An original systematic review: use of artificial intelligence and unmet needs in eosinophilic oesophagitis from COVID-19 era

In this work, we investigated the effectiveness of a digital game-based learning (DGBL) methodology for remote training using DGBL software specifically designed for neonatal resuscitation. The DGBL approach was validated using state-of-the-art statistical methods in a cohort of 52 anesthesiology trainees and compared to a homogeneous retrospective control group of pediatric trainees with comparable prior knowledge, who underwent an in-person training course using the same digital serious game. Scores obtained during each game session were recorded using in-house software and used to assess progress in flowchart knowledge, decision-making time, timing of assisted ventilation, and ability to check equipment. The results confirmed that the DGBL-based remote training approach is a valuable tool that offers an interactive, effective, and engaging learning experience. Future developments will integrate an adaptive AI-based agent to further enhance the game's effectiveness.