The roles of radiomics and deep learning for automatic detection, stability assessment, and rupture risk prediction in intracranial aneurysms: a systematic review.

ABSTRACT:

Background and objectives

Presently, the radiomics and deep learning have achieved notable advancements in the automatic detection, stability assessment, and rupture risk prediction of intracranial aneurysms (IAs). However, there are still certain challenges in data quality, model robustness, and applicability among the published studies. Therefore, this study aims to provide a systematic review of the roles of radiomics and deep learning in the automatic detection, stability assessment, and rupture risk prediction of IAs, with providing insights for the individual stratified management of IAs patients.

Methods

Between January 2015 and December 2024, the literatures were retrieved in PubMed, Web of Science, Embase and the Cochrane Library using a combination of subject headi

SUBMITTER: Yan C 

PROVIDER: S-EPMC12777297 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature