Machine learning models for predicting delayed cerebral ischemia following ruptured intracranial aneurysms: A systematic review and meta-analysis

ML models and particularly ensemble approaches promise to improve DCI prediction after SAH. External validation, model calibration and prospective clinical integration warrant future work.

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Publication Details

Journal
Journal of Stroke and Cerebrovascular Diseases
Published
2026-02-15
DOI
https://doi.org/10.1016/j.jstrokecerebrovasdis.2026.108592
Primary Topic
Intracranial Aneurysms: Treatment and Complications
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine learning models for predicting delayed cerebral ischemia following ruptured intracranial aneurysms: A systematic review and meta-analysis

Carmelo Lucio Sturiale, Matteo Palermo, Alessio Albanese, Francesco Doglietto et al.
Journal of Stroke and Cerebrovascular Diseases
Intracranial Aneurysms: Treatment and Complications
article

Machine learning models for predicting delayed cerebral ischemia following ruptured intracranial aneurysms: A systematic review and meta-analysis

Carmelo Lucio Sturiale, Matteo Palermo, Alessio Albanese, Francesco Doglietto, Alessandro Olivi
article en

Abstract

ML models and particularly ensemble approaches promise to improve DCI prediction after SAH. External validation, model calibration and prospective clinical integration warrant future work.

Journal of Stroke and Cerebrovascular DiseasesVol. 35(4)
Università Cattolica del Sacro Cuore (IT), Agostino Gemelli University Polyclinic (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT)
Openalex Percentile: Top 58%
Intracranial Aneurysms: Treatment and Complications
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