StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records
Determining acute ischemic stroke (AIS) etiology is fundamental to secondary stroke
prevention efforts but can be diagnostically challenging. We trained and validated an …
prevention efforts but can be diagnostically challenging. We trained and validated an …
Artificial intelligence and stroke imaging
The potential benefit of introducing AI to stroke, in imaging and elsewhere, is now
unquestionable, but the optimal approach–and the path to real-world application–remain …
unquestionable, but the optimal approach–and the path to real-world application–remain …
[HTML][HTML] A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata
Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term
functional disabilities without timely intervention. Spatio-temporal (4D) Computed …
functional disabilities without timely intervention. Spatio-temporal (4D) Computed …
Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke
TH Yang, YY Su, CL Tsai, KH Lin, WY Lin… - European journal of …, 2024 - Elsevier
Purpose Clinical risk scores are essential for predicting outcomes in stroke patients. The
advancements in deep learning (DL) techniques provide opportunities to develop prediction …
advancements in deep learning (DL) techniques provide opportunities to develop prediction …
Automatic Prediction of Stroke Treatment Outcomes: Latest Advances and Perspectives
Stroke is a major global health problem that causes mortality and morbidity. Predicting the
outcomes of stroke intervention can facilitate clinical decision-making and improve patient …
outcomes of stroke intervention can facilitate clinical decision-making and improve patient …
Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning
MS von Braun, K Starke, L Peter, D Kürsten, F Welle… - Brain, 2025 - academic.oup.com
The advent of endovascular thrombectomy has significantly improved outcomes for stroke
patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As …
patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As …
Machine learning for early dynamic prediction of functional outcome after stroke
Background Prediction of outcome after stroke is critical for treatment planning and resource
allocation but is complicated by fluctuations during the first days after onset. We propose a …
allocation but is complicated by fluctuations during the first days after onset. We propose a …
Automatic etiological classification of stroke thrombus digital photographs using a deep learning model
Á Lucero-Garófano, A Aliena-Valero… - Frontiers in …, 2025 - frontiersin.org
Background Etiological classification of ischemic stroke is fundamental for secondary
prevention, but frequently results in undetermined cause. We aimed to develop a Deep …
prevention, but frequently results in undetermined cause. We aimed to develop a Deep …
[HTML][HTML] iSPAN: Explainable prediction of outcomes post thrombectomy with Machine Learning
Purpose This study aimed to develop and evaluate a machine learning model and a novel
clinical score for predicting outcomes in stroke patients undergoing endovascular …
clinical score for predicting outcomes in stroke patients undergoing endovascular …
Development and Internal Validation of Machine Learning Models to Predict Mortality and Disability After Mechanical Thrombectomy for Acute Anterior Circulation …
H Hoffman, J Wood, JR Cote, MS Jalal, FO Otite… - World Neurosurgery, 2024 - Elsevier
Objective Mechanical thrombectomy (MT) improves outcomes in patients with LVO but many
still experience mortality or severe disability. We sought to develop machine learning (ML) …
still experience mortality or severe disability. We sought to develop machine learning (ML) …