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This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (3909) Decision Support for Health Professionals (2360) Machine Learning (3353) Stroke (333) Artificial Intelligence (5054) Computer-Aided Diagnosis (445) Applications of AI (1102)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54121, first published .
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Machine Learning for the Early Prediction of Delayed Cerebral Ischemia in Patients With Subarachnoid Hemorrhage: Systematic Review and Meta-Analysis

Machine Learning for the Early Prediction of Delayed Cerebral Ischemia in Patients With Subarachnoid Hemorrhage: Systematic Review and Meta-Analysis

Authors of this article:

Haofuzi Zhang1 Author Orcid Image ;   Peng Zou1 Author Orcid Image ;   Peng Luo1 Author Orcid Image ;   Xiaofan Jiang1 Author Orcid Image
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Journals

  1. Gollwitzer M, Mazanec V, Steindl M, Atli B, Stroh-Holly N, Hauser A, Sardi G, Rossmann T, Aspalter S, Rauch P, Horner E, Sonnberger M, Gruber A, Gmeiner M. Early Prediction of Cerebral Vasospasm After Aneurysmal Subarachnoid Hemorrhage Using a Machine Learning Model and Interactive Web Application. Brain Sciences 2025;15(11):1187 View
  2. Wang R, Qian L, Zeng Y, Cai L, He M, Xu J, Zhang Y. A machine learning predictive model for acute kidney injury among aneurysmal subarachnoid hemorrhage patients. BMC Medical Informatics and Decision Making 2025;25(1) View
  3. Palermo M, D’Arrigo S, Olivi A, Sturiale C. Machine learning models for predicting vasospasm following ruptured intracranial aneurysms: a systematic review and meta-analysis. Acta Neurochirurgica 2025;167(1) View
  4. Willms J, Schmid J, Inauen C, Bögli S, Bienefeld-Seall N, Beck T, Boss J, Keller E. Silent Validation of a Longitudinal Model for Predicting Delayed Cerebral Ischemia in Real Time after Subarachnoid Hemorrhage. NEJM AI 2026;3(2) View
  5. Swiatek V, Schiffner C, Kummer T, Ehrhardt L, Stein K, Rashidi A, Saalfeld S, Werdehausen R, Sandalcioglu I, Neyazi B. Data-Driven Analysis of Systemic Indicators Linking Stroke-Associated Pneumonia, Delayed Cerebral Ischemia, and Outcome After Aneurysmal Subarachnoid Hemorrhage. Journal of Clinical Medicine 2026;15(4):1359 View
  6. Li Y, Zhao K, Wu J. Machine Learning in Left Ventricular Hypertrophy Detection: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2026;28:e76637 View
  7. de Andrade J, de Lima Froio N, Nascimento P, Querobin S, de Oliveira N, Carneiro T. Cerebral Vasospasm Detection and Delayed Cerebral Ischemia Prediction after Aneurysmal Subarachnoid Hemorrhage: A Scoping Review. Neurocritical Care 2026;45(2):853 View
  8. Swiatek V, Kummer T, Swiatek C, Ehrhardt L, Stein K, Rashidi A, Werdehausen R, Sandalcioglu I, Saalfeld S, Neyazi B. Machine Learning-Based Prediction of Delayed Cerebral Ischemia and Functional Outcome in Aneurysmal Subarachnoid Hemorrhage: The Role of CNS Infection-Related Parameters. Biomedicines 2026;14(8):1853 View
  9. Ay M, Tüfek Öztan D, Asri Ş, Karaveli A, Öztürk N, Alparslan A, Avcı Ay S. Phase-Based Dynamic Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: Comparison of a Large Language Model with Intensive Care Specialists. Medicina 2026;62(9):1680 View
  10. Miller J, Davis M, Clark E. Hierarchical Transformer Model with Uncertainty-Aware Attention for Predicting Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage Using Hourly Neurological and Vital Sign Data. Journal of Artificial Intelligence for Healthcare Systems 2026;5(2) View