ArticleNature communications2023
Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep Learning Applications in Imaging of Acute Ischemic Stroke: A Systematic Review and Narrative Summary.Radiology · 2025Pooled it
- Association between uric acid and the risk of hemorrhagic transformation in patients with acute ischemic stroke: a systematic review and meta-analysis.Frontiers in neurology · 2024Pooled it
- Circle of Willis-Guided Localization for Simultaneous Detection and Classification of Large Vessel Occlusions in Brain CTA.Neuroinformatics · 2026Article
- Anatomy- and Time-Based Post-Processing with CT Perfusion-Derived Time-Vessel Maps to Reduce Incorrect Occlusion Detections in Late-Phase CT Angiography.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial intelligence in acute hydrocephalus: Narrowing the diagnostic gap.European radiology · 2026Article
- Swarm Learning for the Detection of Middle Cerebral Artery Occlusion On CT Angiography.Clinical neuroradiology · 2026Article
- Evaluating and Mitigating Carbon Dioxide Equivalent Emissions in Stroke Management: A Modeling Study.Journal of the American Heart Association · 2026Article
- Initial Experience With a Deep Learning Algorithm for Detecting Posterior Circulation Large Vessel Occlusion on Noncontrast Computed Tomography.Stroke (Hoboken, N.J.) · 2026Article
- The Role of AI-Based Software BrainScan in the Interpretation of Non-Contrast Head CT in Acute Ischemic Stroke: An External Validation Study.Neurology international · 2026Article
- Redefining Stroke Care with Artificial Intelligence: Recent Advances.Current neurology and neuroscience reports · 2026Review
- Education Research: Bridging the Artificial Intelligence Training Gap: Evidence from a National Survey of Italian Neurology Residents.Neurology. Education · 2026Article
- Cellular Mechanisms Underlying Endothelial and Histopathological Alterations Induced by Cerebral Angiography.Journal of clinical medicine · 2026Review
- Voxel-accurate MRI-microscopy Correlation Enables AI-powered Prediction of Brain Disease States.Theranostics · 2026Article
- Automatic segmentation of coronary plaques in coronary CT angiography using neural networks.PloS one · 2026Article
- Enhanced diagnostic value of sequential head and neck CTA and MR-DWI in acute ischemic stroke.Medicine · 2025Observational
- A Metalloporphyrin Nanosystem Enables Non-Invasive Visualization and Specific Treatment for Thrombosis and Ischemic Stroke.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Contrast bolus timing in CT-angiography and CT-perfusion: insights from a large clinical dataset.Neuroradiology · 2025Article
- Deep Learning Based Detection of Large Vessel Occlusions in Acute Ischemic Stroke Using High-Resolution Photon Counting Computed Tomography and Conventional Multidetector Computed Tomography.Clinical neuroradiology · 2025Article
- AI and Neurology.Neurological research and practice · 2025Review
- AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.PloS one · 2025Article
Corrections and comments
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Authors and funding
25 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%). Benchmarking against two CE- and FDA-approved software solutions showed significantly higher performance for our ANN with improvements of 25-45% for sensitivity and 4-11% for NPV (p ≤ 0.003 each). We provide an imaging platform ( https://stroke.neuroAI-HD.org ) for online processing of medical imaging data with the developed ANN, including provisions for data crowdsourcing, which will allow continuous refinements and serve as a blueprint to build robust and generalizable AI algorithms.
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