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Review
. 2024 Apr 17:15:1391382.
doi: 10.3389/fneur.2024.1391382. eCollection 2024.

Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images

Zhongjian Wen #  1   2 , Yiren Wang #  1   2 , Yuxin Zhong #  3 , Yiheng Hu  4 , Cheng Yang  5 , Yan Peng  6 , Xiang Zhan  7 , Ping Zhou  2   7 , Zhen Zeng  8
Affiliations
Review

Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images

Zhongjian Wen et al. Front Neurol. .

Abstract

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.

Keywords: artificial intelligence; deep learning; intracranial aneurysm; machine learning; radiomics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Workflow and principles of radiomics and artificial intelligence algorithms. Referenced and reproduced with permission from (1).
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