ArticleThe ultrasound journal2025
Effectiveness of traditional, artificial intelligence-assisted, and virtual reality training modalities for focused cardiac ultrasound skill acquisition: a randomised controlled study.
Article in The ultrasound journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06355557 (Human vs Machine), which is not on this map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Human vs Machine: a Randomised Controlled Trial Comparing Traditional In-person Instruction, Artificial Intelligence Versus Virtual Reality for Learning Basic Critical Care Echocardiography
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Effectiveness of Artificial Intelligence in Undergraduate Health Professions Education: Systematic Review and Meta-Analysis of Randomized Controlled Trials.JMIR medical education · 2026Pooled it
- Artificial Intelligence Improves Apical Four-Chamber Window Quality in Experienced but Not Novice Users.Cureus · 2026Article
- Artificial intelligence in undergraduate medical education clinical skills curricula: a scoping review of implementations since 2022.Frontiers in digital health · 2026Review
- Application of the Flipped Classroom Teaching Model Integrated with the Feynman Learning Method in Cardiovascular Ultrasound Postgraduate Teaching: An Action Research.Advances in medical education and practice · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundFocused cardiac ultrasound (FCU) is increasingly used as an extension of physical examination to aid diagnosis and clinical decision-making. Emerging educational technologies such as artificial intelligence (AI)-enabled ultrasound devices and virtual reality (VR) simulators offer novel, cost-effective and self-directed approaches for FCU skill acquisition training. Prior studies suggest that VR-based training may be non-inferior to traditional teaching, while AI offers real-time feedback to enhance learning.
objectiveThis study aimed to evaluate the effectiveness and non-inferiority of AI and VR-assisted training compared to Traditional in-person instruction in achieving competency in FCU image acquisition. Secondary outcomes included time to acquire an optimal apical 4 chamber (A4C) view and self-reported confidence in image acquisition, assessed immediately post-training and at 3-month follow up.
methodsIn this single-blind, randomized controlled pilot trial, 66 local medical students with no prior FCU experience were randomised into 3 arms: (1) AI-enabled ultrasound training using the Kosmos system, (2) VR-based stimulator (Vimedix), and (3) Traditional instructor-led teaching. All sessions were 60 min long. Image acquisition of 5 standard FCU views was assessed by blinded evaluators using the Rapid Assessment of Competency in Echocardiography (RACE) score at both time points.
resultsTwo participants were lost to follow-up (one each from the AI and VR groups). In the first assessment, the Traditional group achieved the highest mean RACE score (15.77), followed by AI (13.39) and VR (13.23). Non-inferiority testing confirmed that both AI (95% CI -∞ to 3.60; p < 0.001) and VR (95% CI -∞ to 3.58; p < 0.001) methods were non-inferior to Traditional instruction. The AI group achieved the shortest mean time to acquire an optimal A4C view (158 ± 99.1 s), followed by the VR (189 ± 94.7 s), and traditional (199 ± 115.1 s), though differences were not statistically significant (p = 0.591). Confidence levels were initially highest in the Traditional group, while the VR group showed higher confidence at 3-month follow-up, particularly in parasternal long-axis view acquisition.
conclusionsAI and VR-based training methods were non-inferior to traditional instruction for FCU skill acquisition. Both modalities show promise as scalable, technology-enabled alternatives in ultrasound education. Trial registration This trial was registered on Clinicaltrials.gov (NCT06355557).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.