AI-enhanced simulation platforms for ultrasound-guided regional anesthesia: bridging theoretical knowledge and clinical proficiency

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Authors: Wei Liu, Dongmei Ma
Cited by: 0

Abstract

This article looks at the development of artificial intelligence (AI)-enhanced ultrasound-guided regional anesthesia simulation platforms and their use in medical education. As the complexity of regional anesthesia procedures grows, traditional teaching methods fail to address the clinical urgency of reducing preventable complications, such as inadvertent vascular puncture (reported incidence: 4.1–6.8%) and incomplete nerve blockade. These complications not only compromise patient safety, but also highlight a critical “expertise gap” between theoretical knowledge and practical execution. These AI-enabled simulation platforms can provide more realistic clinical scenarios, helping medical students and residents translate theoretical knowledge into practical skills. This review provides a comprehensive analysis of the current technologies, educational outcomes, and their role in enhancing clinical competency in regional anesthesia.

Fields of Study & Subjects

Simulation-Based Education in Healthcare Surgical Simulation and Training Anatomy and Medical Technology

Publication details

Journal / source
Signa Vitae
Pages
3–3
Publication date
8 February 2026