Evidence map›Paper›PMID 37666770›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2023

[Advances in digital twins technology of human skeletal muscle].

Dan Liu, Ling He, Di Yang, Jie Zhang, Jiadui Chen, Guanci Yang

Abstract readEnglish Abstract
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. [Digital twin hospitals: transforming the future of healthcare].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024
    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

6 authors.

Dan LiuKey lab of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, P.R. China.
Ling HeKey lab of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, P.R. China.
Di YangThe First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, P.R. China.
Jie ZhangCollege of Computer Science and Technology, Guizhou University, Guiyang 550025, P.R. China.
Jiadui ChenKey lab of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, P.R. China.
Guanci YangKey lab of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human skeletal muscle drives skeletal movement through contraction. Embedding its functional information into the human morphological framework and constructing a digital twin of skeletal muscle for simulating physical and physiological functions of skeletal muscle are of great significance for the study of "virtual physiological humans". Based on relevant literature both domestically and internationally, this paper firstly summarizes the technical framework for constructing skeletal muscle digital twins, and then provides a review from five aspects including skeletal muscle digital twins modeling technology, skeletal muscle data collection technology, simulation analysis technology, simulation platform and human medical image database. On this basis, it is pointed out that further research is needed in areas such as skeletal muscle model generalization, accuracy improvement, and model coupling. The methods and means of constructing skeletal muscle digital twins summarized in the paper are expected to provide reference for researchers in this field, and the development direction pointed out can serve as the next focus of research.

Indexed as

MovementTechnologyComputer SimulationDatabases, FactualHumansMuscle, SkeletalData collection technologyDigital twins modelingHuman medical image databaseSimulation analysisSimulation platformSkeletal muscle digital twins

Identifiers

PMID37666770
PMCPMC10477387

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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.