Evidence map›Paper›PMID 41322471›Full record

ArticleFrontiers in artificial intelligence2025

A hybrid deep learning framework for SEM-based air pollutant analysis: Mamba integration and GAN-augmented training.

Minyi Cao, Derun Kong, Guoying Zhu, Zhongwen Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in artificial intelligence, 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.

Minyi CaoJiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China.
Derun KongSchool of Resources and Environment, Nanchang University, Nanchang, Jiangxi, China.
Guoying ZhuJiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China.
Zhongwen ChenJiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution poses severe threats to public health and ecological stability, making accurate analysis of airborne pollutant composition increasingly vital. In this paper, we propose a novel deep learning framework for efficient classification of pollutant components based on microscopic or spectral images. The proposed model integrates the recent

Indexed as

air pollutionenvironmental monitoringGAN-generated dataMamba mechanismpollutant component analysis

Identifiers

PMID41322471
PMCPMC12660190

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LicenceCC BY
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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.