Evidence map›Paper›PMID 41152171›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2025

[The design and application of a genu valgum gait recognition model based on triple attention mechanism and spatial hierarchical pooling strategy].

Xiaoneng Song, Kun Qian, Xuan Hou, Yizhe Wang

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, 2025. 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
–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

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

4 authors.

Xiaoneng SongDepartment of Physical Education, Jiangnan University, Wuxi, Jiangsu 214122, P. R. China.
Kun QianSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, P. R. China.
Xuan HouSchool of Innovation Engineering, Macau University of Science and Technology, Macau SAR 0999078, P. R. China.
Yizhe WangSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong 518172, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To facilitate the early intelligent screening of pediatric genu valgum, this study develops a deep learning-based gait recognition model tailored for clinical application. The model is constructed upon a three-dimensional residual network architecture and incorporates a triplet attention module alongside a spatial hierarchical pooling module, jointly enhancing feature interaction across temporal, spatial, and channel dimensions. This design ensures an optimal balance between representational capacity and computational efficiency. Evaluated on a self-constructed dataset, the model achieves precision of 98.0%, 97.1%, and 96.5%, recall rates of 97.5%, 97.0%, and 95.0%, and F

Indexed as

Deep LearningGaitGenu ValgumAlgorithmsChildHumansNeural Networks, ComputerGait recognitionGenu valgumSpatial hierarchical pooling moduleTriple attention module

Identifiers

PMID41152171
PMCPMC12568726

What OpenQuestion 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 OpenQuestion graph.