Development and validation of a deep learning model for prediction of intracranial aneurysm rupture risk based on multi-omics factor-Reference-Cited by-同舟云学术

Development and validation of a deep learning model for prediction of intracranial aneurysm rupture risk based on multi-omics factor

Published:2023-04-26 Issue:10 Volume:33 Page:6759-6770
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Turhon Mirzat,Li Mengxing,Kang Huibin,Huang Jiliang,Zhang Fujunhui,Zhang Ying,Zhang Yisen,Maimaiti Aierpati,Gheyret Dilmurat,Axier Aximujiang,Aisha Miamaitili,Yang Xinjian,Liu Jian

Funder

National Natural Science Foundation of China

Beijing Municipal Administration of Hospitals Incubating Program

Research Projects of National Health Commission Capacity Building and Continuing Education Center in 2021

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-09672-3.pdf

Reference27 articles.

1. Li MH, Chen SW, Li YD et al (2013) Prevalence of unruptured cerebral aneurysms in Chinese adults aged 35 to 75 years: a cross-sectional study. Ann Intern Med 159:514–521

2. Hackenberg KAM, Hänggi D, Etminan N (2018) Unruptured intracranial aneurysms. Stroke 49(9):2268–2275

3. Morita A, Kirino T, Hashi K et al (2012) The natural course of unruptured cerebral aneurysms in a Japanese cohort. New Engl J Med 366:2474–2482

4. Korja M, Kivisaari R, Rezai Jahromi B et al (2017) Natural history of ruptured but untreated intracranial aneurysms. Stroke 48:1081–1084

5. Algra AM, Lindgren A, Vergouwen MDI et al (2019) Procedural clinical complications, case-fatality risks, and risk factors in endovascular and neurosurgical treatment of unruptured intracranial aneurysms: a systematic review and meta-analysis. JAMA Neurol 76(3):282–293

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