Evidence map›Paper›PMID 37547140›Full record

ArticleFrontiers in neuroscience2023

Machine learning analysis reveals aberrant dynamic changes in amplitude of low-frequency fluctuations among patients with retinal detachment.

Yu Ji, Yuan-Yuan Wang, Qi Cheng, Wen-Wen Fu, Shui-Qin Huang, Pei-Pei Zhong, Xiao-Lin Chen, Ben-Liang Shu, Bin Wei, Qin-Yi Huang and 1 more

Abstract read
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Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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

11 authors.

Yu JiDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Yuan-Yuan WangDepartment of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Qi ChengDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Wen-Wen FuDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Shui-Qin HuangDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Pei-Pei ZhongDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Xiao-Lin ChenDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Ben-Liang ShuDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Bin WeiDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Qin-Yi HuangDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Xiao-Rong WuDepartment of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is increasing evidence that patients with retinal detachment (RD) have aberrant brain activity. However, neuroimaging investigations remain focused on static changes in brain activity among RD patients. There is limited knowledge regarding the characteristics of dynamic brain activity in RD patients. Aim: This study evaluated changes in dynamic brain activity among RD patients, using a dynamic amplitude of low-frequency fluctuation (dALFF), k-means clustering method and support vector machine (SVM) classification approach. Methods: We investigated inter-group disparities of dALFF indices under three different time window sizes using resting-state functional magnetic resonance imaging (rs-fMRI) data from 23 RD patients and 24 demographically matched healthy controls (HCs). The k-means clustering method was performed to analyze specific dALFF states and related temporal properties. Additionally, we selected altered dALFF values under three distinct conditions as classification features for distinguishing RD patients from HCs using an SVM classifier. Results: RD patients exhibited dynamic changes in local intrinsic indicators of brain activity. Compared with HCs, RD patients displayed increased dALFF in the bilateral middle frontal gyrus, left putamen (Putamen_L), left superior occipital gyrus (Occipital_Sup_L), left middle occipital gyrus (Occipital_Mid_L), right calcarine (Calcarine_R), right middle temporal gyrus (Temporal_Mid_R), and right inferior frontal gyrus (Frontal_Inf_Tri_R). Additionally, RD patients showed significantly decreased dALFF values in the right superior parietal gyrus (Parietal_Sup_R) and right paracentral lobule (Paracentral_Lobule_R) [two-tailed, voxel-level Conclusion: Our findings offer important insights concerning the neuropathology that underlies RD and provide robust evidence that dALFF, a local indicator of brain activity, may be useful for clinical diagnosis.

Indexed as

brain regiondynamic amplitude of low-frequency fluctuationk-means clustering methodresting-state functional magnetic resonance imagingretinal detachmentsliding windowsupport vector machine

Identifiers

PMID37547140
PMCPMC10398337

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