What are the current applications of artificial intelligence in point of care ultrasound education?
File(s)
Preprint
Author(s)
Foster, Patrick
Aftab, Ali
Type
preprint
Abstract
Background Point of care ultrasound (POCUS) is an increasingly important clinical skill. The rise of artificial intelligence (AI) in medical imaging offers opportunities to enhance POCUS education, yet access to structured curriculum integrated AI teaching remains limited. This review seeks to explore the application of AI in POCUS education. Methodology A systematic Embase search identified studies evaluating AI in ultrasound education. Inclusion criteria focused on clinical learners and how AI tools were being integrated into their POCUS learning. Thirty-two studies were evaluated using a narrative synthesis method. There was considerable heterogenicity in study design. Findings The highest proportion of studies took place in a perioperative and surgical setting (44%). 47% of the studies evaluated learning outcomes whilst integrating AI tools into the learning program, while the remainder examined applications with educational implications. Four themes emerged from the review: 1. Enhanced anatomical learning through segmentation and highlighting 2. Real time image acquisition guidance 3. Standardised imaging protocols 4. Patient safety during self-directed learning A majority of studies showed improved learner performance, reduced errors or accelerated skill acquisition.
Date Issued
2025-12-17
Citation
Elsevier BV, 2025
Journal / Book Title
Elsevier BV
Copyright Statement
© 2025 The Author(s).