ArticleJournal of healthcare engineering2021
VR/AR Technology in Human Anatomy Teaching and Operation Training.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Enhancing anatomy education with virtual reality: integrating three-dimensional models for improved learning efficiency and student satisfaction.Frontiers in medicine · 2025Review
- Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review.Global challenges (Hoboken, NJ) · 2024Review
- Retracted: VR/AR Technology in Human Anatomy Teaching and Operation Training.Journal of healthcare engineering · 2023Article
- Digital Transformation Will Change Medical Education and Rehabilitation in Spine Surgery.Medicina (Kaunas, Lithuania) · 2022Article
Corrections and comments
- Retraction · 2023-05-24Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AR/VR technology can fuse the clinical imaging data and information to build an anatomical environment combining virtual and real, which is helpful to improve the interest of teaching and the learning initiative of medical students, and then improve the effect of clinical teaching. This paper studies the application and learning effect of the VR/AR system in human anatomy surgery teaching. This paper first shows the learning environment and platform of the VR/AR system, then explains the interface and operation of the system, and evaluates the teaching situation. This paper takes the VR/AR operation simulation system of an Irish company as an example and evaluates the learning effect of 41 students in our hospital. Research shows that the introduction of the feature reweighting module in the VR/AR surgery simulation system improves the accuracy of bone structure segmentation (IOU value increases from 79.62% to 83.56%). For real human ultrasound image data, the IOU value increases from 80.21% to 82.23% after the feature reweighting module is introduced. Therefore, the dense convolution module and feature reweighting module improve the learning ability of the network for bone structure features in ultrasound images from two aspects of feature connection and importance understanding and effectively improve the performance of bone structure segmentation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.