Evidence map›Paper›PMID 41760211›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2026

[A multi-source information fusion-based method for the local pulse wave velocity estimation in carotid artery].

Zhi Chen, Li Deng, Yufeng Zhang, Dawen Xia, Wenxia Song, Youjun Lu, Xin Wang, Yi An

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zhi ChenSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.
Li DengSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.
Yufeng ZhangDepartment of Electronic Engineering, Information School, Yunnan University, Kunming 650000, P. R. China.
Dawen XiaEngineering Research Center for Micro Nano and Intelligent Manufacturing, Ministry of Education, Kaili College, Kaili, Guizhou 556011, P. R. China.
Wenxia SongSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.
Youjun LuSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.
Xin WangSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.
Yi AnSchool of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aiming at the limitations of low accuracy and poor stability in the transit time method for estimating carotid local pulse wave velocity, this paper proposed a machine learning-based local pulse wave velocity estimation method, which integrated carotid pulse wave time-domain features, age, and cardiac function parameters. The research was based on a dataset of carotid pulse wave propagation from 4 374 virtual subjects. By combining the Pearson correlation coefficient method and the least absolute shrinkage and selection algorithm to select multi-position combinations of pulse wave time-domain features, and integrating age, heart rate, and other parameters as input features, five machine learning models including multiple linear regression, Bayesian ridge regression,

Indexed as

Carotid ArteriesMachine LearningPulse Wave AnalysisSignal Processing, Computer-AssistedAlgorithmsBayes TheoremConvolutional Neural NetworksHumansNeural Networks, ComputerSupport Vector MachineCarotid arteryLocal pulse wave velocityMachine learningTime-domain feature

Identifiers

PMID41760211
PMCPMC12948540

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Registered trials

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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.