Evidence map›Paper›PMID 38192576›Full record

ArticleFrontiers in neurology2023

Research on prognostic risk assessment model for acute ischemic stroke based on imaging and multidimensional data.

Jiabin Liang, Jie Feng, Zhijie Lin, Jinbo Wei, Xun Luo, Qing Mei Wang, Bingjie He, Hanwei Chen, Yufeng Ye

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2023. 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
0.4field-weighted citation impact, top 31% 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

9 authors at 6 institutions in 2 countries.

Jiabin Liang *Postgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
Jie Feng *Radiology Department of Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Zhijie Lin *Laboratory for Intelligent Information Processing, Guangdong University of Technology, Guangzhou, China.
Jinbo WeiPostgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
Xun LuoKerry Rehabilitation Medicine Research Institute, Shenzhen, China.
Qing Mei WangStroke Biological Recovery Laboratory, Spaulding Rehabilitation Hospital, Teaching Affiliate of Harvard Medical School, Charlestown, MA, United States.
Bingjie HePanyu Health Management Center, Guangzhou, China.
Hanwei ChenPostgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
Yufeng YePostgraduate Cultivation Base of Guangzhou University of Chinese Medicine, Panyu Central Hospital, Guangzhou, China.
Guangzhou University of Chinese Medicine · CNPanyu District Central Hospital · CNGuangdong Institute of Intelligent Manufacturing · CNPanyu Hospital of Chinese Medicine · CNSpaulding Rehabilitation Hospital · USSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurately assessing the prognostic outcomes of patients with acute ischemic stroke and adjusting treatment plans in a timely manner for those with poor prognosis is crucial for intervening in modifiable risk factors. However, there is still controversy regarding the correlation between imaging-based predictions of complications in acute ischemic stroke. To address this, we developed a cross-modal attention module for integrating multidimensional data, including clinical information, imaging features, treatment plans, prognosis, and complications, to achieve complementary advantages. The fused features preserve magnetic resonance imaging (MRI) characteristics while supplementing clinical relevant information, providing a more comprehensive and informative basis for clinical diagnosis and treatment. The proposed framework based on multidimensional data for activity of daily living (ADL) scoring in patients with acute ischemic stroke demonstrates higher accuracy compared to other state-of-the-art network models, and ablation experiments confirm the effectiveness of each module in the framework.

Indexed as

acute ischemic strokeassessment modelimagingMRImultidimensional dataprognostic risk

Identifiers

PMID38192576
PMCPMC10773779
OpenAlexW4389951114

What OpenQuestion holds

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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.