Evidence map›Paper›PMID 34671228›Full record

ArticleContrast media & molecular imaging2021

Magnetic Resonance Imaging Features under Deep Learning Algorithms in Evaluated Cerebral Protection of Craniotomy Evacuation of Hematoma under Propofol Anesthesia.

Deqian Xin, Zhongzhe An, Juan Ding, Zhi Li, Leyan Qiao

Open access · hybridAbstract read
In one paragraph

Article in Contrast media & molecular imaging, 2021. 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
0.1field-weighted citation impact, top 50% 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, 1 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.

Deqian XinDepartment of Anesthesiology, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China.ORCID 0000-0002-1313-859X
Zhongzhe AnDepartment of Anesthesiology, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China.ORCID 0000-0003-1955-9691
Juan DingDepartment of Allergy, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China.ORCID 0000-0003-1943-870X
Zhi LiDepartment of Anesthesiology, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China.ORCID 0000-0003-4843-5129
Leyan QiaoDepartment of Anesthesiology, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China.ORCID 0000-0002-6016-2146
Yuhuangding Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to explore the value of magnetic resonance imaging (MRI) features based on deep learning super-resolution algorithms in evaluating the value of propofol anesthesia for brain protection of patients undergoing craniotomy evacuation of the hematoma. An optimized super-resolution algorithm was obtained through the multiscale network reconstruction model based on the traditional algorithm. A total of 100 patients undergoing craniotomy evacuation of hematoma were recruited and rolled into sevoflurane control group and propofol experimental group. Both were evaluated using diffusion tensor imaging (DTI) images based on deep learning super-resolution algorithms. The results showed that the fractional anisotropic image (FA) value of the hind limb corticospinal tract of the affected side of the internal capsule of the experimental group after the operation was 0.67 ± 0.28. The National Institute of Health Stroke Scale (NIHSS) score was 6.14 ± 3.29. The oxygen saturation in jugular venous (SjvO

Indexed as

Magnetic Resonance ImagingAdultAgedBrainCraniotomyDeep LearningDiffusion Tensor ImagingFemaleHematomaHumansJugular VeinsMaleMiddle AgedOxygen SaturationPhosphopyruvate HydratasePropofolENO2 protein, humanPhosphopyruvate HydratasePropofolSevoflurane

Identifiers

PMID34671228
PMCPMC8500760
OpenAlexW3204745577

What OpenQuestion holds

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LicenceCC BY
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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.