logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Altered Brain Structure Age Gap Estimation In Major Depressive Disorder Patients With And Without Anhedonia A Machine Learningbased Study Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu

  • SKU: BELL-238773392
Altered Brain Structure Age Gap Estimation In Major Depressive Disorder Patients With And Without Anhedonia A Machine Learningbased Study Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu
$ 35.00 $ 45.00 (-22%)

4.8

104 reviews

Altered Brain Structure Age Gap Estimation In Major Depressive Disorder Patients With And Without Anhedonia A Machine Learningbased Study Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu instant download after payment.

Publisher: x
File Extension: PDF
File size: 1.43 MB
Author: Qingli Mu & Kejing Zhang & Yue Chen & Yuwei Xu & Shaohua Hu & Manli Huang & Peng Zhang & Dong Cui & Shaojia Lu
Language: English
Year: 2025

Product desciption

Altered Brain Structure Age Gap Estimation In Major Depressive Disorder Patients With And Without Anhedonia A Machine Learningbased Study Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu by Qingli Mu & Kejing Zhang & Yue Chen & Yuwei Xu & Shaohua Hu & Manli Huang & Peng Zhang & Dong Cui & Shaojia Lu instant download after payment.

Translational Psychiatry, doi:10.1038/s41398-025-03555-5

Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it stillremains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain aging inspecific regions. A total of 31 MDD with anhedonia (MDD-WA), 41 MDD without anhedonia (MDD-WoA), and 43 healthy controls(HCs) were recruited in this study. The difference between brain structure age (BSA) applied by support vector regression (SVR) andchronological age was calculated to derive the brain structure age gap estimation (BSAGE). Analyses of covariance (ANCOVAs) and1234567890();,:intergroup comparisons were performed to obtain brain regions with significant BSAGE differences among three groups. Moreover,a support vector machine (SVM) classification model was used to verify the diagnostic value of altered BSAGE. ANCOVAs revealedsignificant BSAGE differences among three groups in the bilateral putamen (PU), left cerebellar white matter (CB), left cuneus (CUN),left fusiform gyrus (FuG), left subcallosal area (SCA), left superior occipital gyrus (SOG), left triangular inferior frontal gyrus (IFG-Tri),right lateral ventricle (L-V), right superior frontal gyrus medial segment (SFG-SM), right opercular inferior frontal gyrus (IFG-Oper),right precuneus (pre-CUN), right posterior insula (INS-Post), and right superior temporal gyrus (STG). Compared to HCs, the MDDWA group showed significant BSAGE increase in all of the aforementioned brain regions, while the MDD-WoA group showedlimited BSAGE increase in the CB, FuG, and SCA of left hemisphere only. However, no significant difference was found betweenMDD-WA and MDD-WoA. The altered BSAGE values showed promising discriminatory performance with an area under the curve(AUC) of 0.944 in classifying MDD-WA and HCs. The current findings emphasize that MDD with anhedonia may exhibit moreextensive advanced brain agi