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Brain Ischemia

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A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Nature communications
Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recommended as the standard diagnosis tool; yet, interpretation can be time-consuming and challenging. We present a specific deep-learning-based model trai...

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients.

Annals of clinical and translational neurology
OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course ...

Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Currently, it is challenging to detect acute ischemic stroke (AIS)-related changes on computed tomography (CT) images. Therefore, we aimed to develop and evaluate an automatic AIS detection system involving a two-stage deep ...

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...

The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model.

Sensors (Basel, Switzerland)
As is known, cerebral stroke has become one of the main diseases endangering people's health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the inci...

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

Japanese journal of radiology
PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense middle cerebral artery sign (HMCAS) on non-contrast computed tomography in comparison with the diagnostic performance of neuroradiologists.

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks.

Journal of neurointerventional surgery
BACKGROUND AND PURPOSE: Infarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in cli...

Integration of ultra-high-pressure liquid chromatography-tandem mass spectrometry with machine learning for identifying fatty acid metabolite biomarkers of ischemic stroke.

Chemical communications (Cambridge, England)
We report for the first time the integration of ultra-high-pressure liquid chromatography-tandem mass spectrometry with machine learning for identifying fatty acid metabolite biomarkers of ischemic stroke. In particular, we develop an optimal model t...

Platelet-rich emboli are associated with von Willebrand factor levels and have poorer revascularization outcomes.

Journal of neurointerventional surgery
BACKGROUND AND AIMS: Platelets and von Willebrand factor (vWF) are key factors in thrombosis and thus are likely key components of acute ischemic stroke (AIS) emboli. We aimed to characterize platelet and vWF levels in AIS emboli and to assess associ...