ArticleCureus2026
Artificial Intelligence Improves Apical Four-Chamber Window Quality in Experienced but Not Novice Users.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe most current point-of-care ultrasound (POCUS) machines incorporate artificial intelligence (AI) features to assist users in obtaining cardiac windows. Prior studies have focused on evaluating the helpfulness of AI acquisition assistance for novice users. This study sought to determine the immediate effect of AI assistance on acquisition time and image quality of apical four-chamber (A4C) cardiac ultrasound windows obtained by both novice and experienced users.
methodsFourteen novices with limited POCUS training during medical school and 10 experienced second- and third-year emergency medicine residents recorded A4C windows with and without AI assistance on three standardized patients in randomized order. Acquisition time in seconds was compared with the Mann-Whitney U test. Chi-square analysis was used to compare the proportion of recordings demonstrating each of the three image quality criteria: all essential structures visible, correct image plane, and proper probe placement.
resultsThe median (interquartile range) acquisition time was longer with AI assistance in both user groups, though the difference was only significant for the novice users (136 (109) seconds; 75 (66); p < .01), not for the experienced users (98 (132); 66 (47); p = .18). All A4C quality criteria were significantly more likely by experienced than novice users. For experienced users, the visibility of all essential structures trended more likely with AI assistance (0.87 (0.70, 0.95); 0.67 (0.49, 0.81); p = .06) and the correct imaging plane was significantly more likely with AI assistance (0.60 (0.42, 0.75); 0.37 (0.22, 0.55); p = .03). There was no difference in proper probe placement with AI assistance for experienced users. No significant differences in image quality criteria were observed in the novice user subgroup.
conclusionThe results provide strong evidence that the immediate effect of AI assistance was associated with longer acquisition times in novice users obtaining A4C windows, with a similar trend among experienced users. AI assistance was also associated with a higher proportion of quality criteria amongst the experienced users, but not the novice users. Therefore, medical educators should consider the experience level of POCUS learners when incorporating AI acquisition features into education and clinical practice.
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