Dynamic evolution of brain structural patterns in liver transplantation recipients: a longitudinal study based on 3D convolutional neuronal network model-Reference-Cited by-同舟云学术

Dynamic evolution of brain structural patterns in liver transplantation recipients: a longitudinal study based on 3D convolutional neuronal network model

Published:2023-04-04 Issue:9 Volume:33 Page:6134-6144
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Cheng Yue,Zhang Xiao-Dong,Chen Cheng,He Ling-Fei,Li Fang-Fei,Lu Zi-Ning,Man Wei-Qi,Zhao Yu-Jiao,Chang Zhi-Xing,Wu Ying,Shen Wen,Fan Ling-Zhong,Xu Jun-Hai

Funder

Natural Science Foundation of Tianjin City

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-09604-1.pdf

Reference40 articles.

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2. Lin WC, Hsu TW, Chen CL et al (2014) Reestablishing brain networks in patients without overt hepatic encephalopathy after liver transplantation. J Cereb Blood Flow Metab 34:1877–1886

3. Cole JH, Franke K (2017) Predicting age using neuroimaging: innovative brain ageing biomarkers. Trends Neurosci 40:681–690

4. Baecker L, Garcia-Dias R, Vieira S, Scarpazza C, Mechelli A (2021) Machine learning for brain age prediction: Introduction to methods and clinical applications. EBioMedicine 72:103600

5. Schnack HG, van Haren NE, Nieuwenhuis M, Hulshoff Pol HE, Cahn W, Kahn RS (2016) Accelerated brain aging in schizophrenia: a longitudinal pattern recognition study. Am J Psychiatry 173:607–616

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