Evidence map›Paper›PMID 35795772›Full record

ArticleComputational intelligence and neuroscience2022

Evaluation on Effect of Acupoint Application to Treat Idiopathic Edema of Perimenopausal Women Using the Segmentation Dictionary Learning Algorithm.

Jinfeng Li, Jiao Wang, Wenxia Zhao, Pei Wang, Min Li

Open access · hybridAbstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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
0.6field-weighted citation impact, top 26% of its field
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, 2 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Jinfeng LiCentre of Traditional Chinese Medical Science, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing 101149, China.ORCID https://orcid.org/0000-0002-0563-1640
Jiao WangCentre of Traditional Chinese Medical Science, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing 101149, China.ORCID https://orcid.org/0000-0003-0256-307X
Wenxia ZhaoCentre of Traditional Chinese Medical Science, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing 101149, China.ORCID https://orcid.org/0000-0002-1701-3671
Pei WangCentre of Traditional Chinese Medical Science, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing 101149, China.ORCID https://orcid.org/0000-0002-5782-4209
Min LiCentre of Traditional Chinese Medical Science, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing 101149, China.ORCID https://orcid.org/0000-0001-7853-9602
Beijing Luhe Hospital Affiliated to Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to explore the effect of ultrasound imaging in the diagnosis and evaluation of acupoint application in the treatment of idiopathic edema. In this study, an ultrasound imaging diagnosis based on the segmentation dictionary learning (S-DL) algorithm was proposed. In addition, the autoencoding algorithm (ASE) was compared with the traditional dictionary learning (DL) algorithm. The treatment effect, associated quantitative integral, and quality of life score of patients in two groups were compared. The results showed that the peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and structural similarity (SSIM) of the S-DL algorithm were 32.45 dB, 0.654, and 0.0012, respectively, which were quite different compared to the ASE and DL algorithms, showing statistical significance (

Indexed as

Acupuncture PointsImage Processing, Computer-AssistedAlgorithmsEdemaFemaleHumansPerimenopauseQuality of Life

Identifiers

PMID35795772
PMCPMC9252663
OpenAlexW4283650532

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.