Revolutionizing Aneurysm detection: The role of artificial intelligence in reducing rupture rates
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10143-024-02636-1.pdf
Reference5 articles.
1. Thompson BG, Brown RD, Amin-Hanjani S, Broderick JP, Cockroft KM, Connolly ES et al (2015) Guidelines for the management of patients with unruptured intracranial aneurysms. Stroke 46:2368–2400. https://doi.org/10.1161/STR.0000000000000070
2. Maeda Y, Ikawa F, Kuwabara M, Hosogai M, Ishii D, Morimoto T et al (2024) Declining trend in the estimated annual rupture rate of unruptured cerebral aneurysms in Japan: a nationwide study. Neurosurg Rev 47:336. https://doi.org/10.1007/s10143-024-02587-7
3. Heit JJ, Honce JM, Yedavalli VS, Baccin CE, Tatit RT, Copeland K et al (2022) RAPID aneurysm: Artificial intelligence for unruptured cerebral aneurysm detection on CT angiography. J Stroke Cerebrovasc Dis 31:106690. https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106690
4. Habibi MA, Fakhfouri A, Mirjani MS, Razavi A, Mortezaei A, Soleimani Y et al (2024) Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants. Neurosurg Rev 47:34. https://doi.org/10.1007/s10143-023-02271-2
5. Cao H, Zeng H, Lv L, Wang Q, Ouyang H, Gui L et al (2024) Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model. Front Physiol 15. https://doi.org/10.3389/fphys.2024.1293380
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