Stroke: Early Recognition and Emergency Management
Abstract
The early recognition and rapid emergency management of acute stroke are pivotal in minimizing permanent neurological damage and reducing global mortality rates. This paper proposes a comprehensive, integrated framework that bridges advanced medical imaging analysis with intelligent emergency coordination systems. By leveraging explainable artificial intelligence for initial lesion assessment and ontology-based cloud computing for resource routing, the system ensures both diagnostic safety and logistical efficiency. Ultimately, this unified approach aims to accelerate treatment timelines, overcoming the fragmented nature of traditional emergency healthcare networks.
References
Chowdhury, R. P., & Rahman, T. (2025). Segmentation of Ischemic Stroke Lesions using Transfer Learning on Multi-sequence MRI. https://arxiv.org/pdf/2511.07281v1 https://arxiv.org/pdf/2511.07281v1
Xu, Weijin, Sha, Zhuang, Yang, Huihua, Jiang, Rongcai, Li, Zhanying, Liu, Wentao, & Su, Ruisheng (2024). An Automatic Cascaded Model for Hemorrhagic Stroke Segmentation and Hemorrhagic Volume Estimation. https://arxiv.org/pdf/2401.04570v1 https://arxiv.org/pdf/2401.04570v1
Bertels, Jeroen, Robben, David, Vandermeulen, Dirk, & Lemmens, Robin (2022). Final infarct prediction in acute ischemic stroke. https://arxiv.org/pdf/2211.04850v1 https://arxiv.org/pdf/2211.04850v1
Tangwiriyasakul, Chayanin, Borges, Pedro, Moriconi, Stefano, Wright, Paul, Mah, Yee-Haur, Teo, James, Nachev, Parashkev, Ourselin, Sebastien, & Cardoso, M. Jorge (2024). Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study. https://arxiv.org/pdf/2404.04025v1 https://arxiv.org/pdf/2404.04025v1
Bi, Huibo, & Gelenbe, Erol (2019). Emergency Management Systems and Algorithms: a Comprehensive Survey. https://arxiv.org/pdf/1907.04136v1 https://arxiv.org/pdf/1907.04136v1
Islam, Md Rashadul (2026). An Explainable Agentic AI Framework for Uncertainty-Aware and Abstention-Enabled Acute Ischemic Stroke Imaging Decisions. https://arxiv.org/pdf/2601.01008v1 https://arxiv.org/pdf/2601.01008v1
A, Bhuvaneswari., & Karpagam, Dr. G. R. (2011). Ontology-Based Emergency Management System in a Social Cloud. https://arxiv.org/pdf/1112.2067v1 https://arxiv.org/pdf/1112.2067v1
González, Mario Pascual (2023). Fuzzy Information Seeded Region Growing for Automated Lesions After Stroke Segmentation in MR Brain Images. https://arxiv.org/pdf/2311.11742v1 https://arxiv.org/pdf/2311.11742v1
Pan, Haonan, Chen, Shuheng, Pishgar, Elham, Alaei, Kamiar, Placencia, Greg, & Pishgar, Maryam (2025). Machine Learning-Based Model for Postoperative Stroke Prediction in Coronary Artery Disease. https://arxiv.org/pdf/2503.11973v1 https://arxiv.org/pdf/2503.11973v1
