Evidence map›Paper›PMID 38390033›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2023

Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI.

Lintao Zhang, Jinjian Wu, Lihong Wang, Li Wang, David C Steffens, Shijun Qiu, Guy G Potter, Mingxia Liu

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Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 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
–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

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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

8 authors.

Lintao ZhangDepartment of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Jinjian WuThe First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Lihong WangDepartment of Psychiatry, University of Connecticut School of Medicine, University of Connecticut, Farmington, CT, USA.
Li WangDepartment of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
David C SteffensDepartment of Psychiatry, University of Connecticut School of Medicine, University of Connecticut, Farmington, CT, USA.
Shijun QiuThe First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Guy G PotterDepartment of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.
Mingxia LiuDepartment of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Funding

2/2 Phenotype Predictors of Cognitive Outcomes in Geriatric DepressionR01MH108560 · NIMH · DUKE UNIVERSITY · PI POTTER, GUY GLENN · 2016 to 2020
$1.8M
Multi-Site Neuroimage Harmonization for Personalized Brain Disorder AnalysisRF1AG073297 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIU, MINGXIA · 2022 to 2022
$1.4M
NIA NIH HHS RF1 AG073297NIMH NIH HHS R01 MH108560
6 · The paper itself

Abstract

Brain structural MRI has been widely used for assessing future progression of cognitive impairment (CI) based on learning-based methods. Previous studies generally suffer from the limited number of labeled training data, while there exists a huge amount of MRIs in large-scale public databases. Even without task-specific label information, brain anatomical structures provided by these MRIs can be used to boost learning performance intuitively. Unfortunately, existing research seldom takes advantage of such brain anatomy prior. To this end, this paper proposes a brain anatomy-guided representation (BAR) learning framework for assessing the clinical progression of cognitive impairment with T1-weighted MRIs. The BAR consists of a

Indexed as

Brain anatomyCognitive impairmentStructural MRI

Identifiers

PMID38390033
PMCPMC10883230

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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.