Evidence map›Paper›PMID 39673002›Full record

ReviewCurrent medical science2024

Artificial Intelligence in Medical Metaverse: Applications, Challenges, and Future Prospects.

Jia-Ming Yang, Bao-Jun Chen, Rui-Yuan Li, Bi-Qiang Huang, Mo-Han Zhao, Peng-Ran Liu, Jia-Yao Zhang, Zhe-Wei Ye

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current medical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Virtual Reality Technology in Otolaryngology Patient Care Management: A Narrative Review of Current Evidence and Future Prospects.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jia-Ming Yang *Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Bao-Jun Chen *Department of Orthopedics, the People's Hospital of Liaoning Province, Shenyang, 110000, China.
Rui-Yuan Li *Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Bi-Qiang HuangChengdu Hua Yu Tianfu Digital Technology Co., Ltd., Chengdu, 610000, China.
Mo-Han ZhaoChengdu Hua Yu Tianfu Digital Technology Co., Ltd., Chengdu, 610000, China.
Peng-Ran LiuDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. lprlprlprwd@163.com.
Jia-Yao ZhangDepartment of Orthopedics, Fuzhou University Affiliated Provincial Hospital, Fuzhou, 350013, China. 459882800@qq.com.
Zhe-Wei YeDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. yezhewei@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The medical metaverse is a combination of medicine, computer science, information technology and other cutting-edge technologies. It redefines the method of information interaction about doctor-patient communication, medical education and research through the integration of medical data, knowledge and services in a virtual environment. Artificial intelligence (AI) is a discipline that uses computer technology to study and develop human intelligence. AI has infiltrated every aspect of medical metaverse and is deeply integrated with the technologies that build medical metaverse, such as large language models (LLMs), digital twins, blockchain and extended reality (including VR/AR/XR). AI has become an integral part of the medical metaverse building process. Moreover, AI also provides richer medical metaverse functions, including diagnosis, education, and consulting. This paper aims to introduce how AI supports the development of medical metaverse, including its specific application scenarios, shortcomings and future development. Our goal is to contribute to the advancement of more sophisticated and intelligent medical methods.

Indexed as

Artificial IntelligenceBiomedical ResearchEducation, MedicalHumansPhysician-Patient Relationsartificial intelligencediagnosiseducationmedical metaversescientific researchtreatment

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.