Quantifying the extent and evolution of cerebral edema developing after stroke is an
important but challenging goal. Lesional net water uptake (NWU) is a promising CT-based …

Background: Hematoma and perihematomal edema volumes are important radiographic
markers in spontaneous intracerebral hemorrhage. Accurate, reliable, and efficient …

The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …

Objectives We aimed to predict hematoma expansion in intracerebral hemorrhage (ICH)
patients by using the deep learning technique. Methods We retrospectively collected data …

Background: Deep learning (DL)-assisted detection and segmentation of intracranial
hemorrhage stroke in noncontrast computed tomography (NCCT) scans are well …

We attempt to generate a definition of delayed perihematomal edema expansion (DPE) and
analyze its time course, risk factors, and clinical outcomes. A multi-cohort data was derived …

Methods We review the use of AI and ML algorithms to assist clinicians in the diagnosis and
management of ischemic stroke, hemorrhagic stroke, intracranial aneurysms, and …

Background: The objective of this study was to assess the performance of the first publicly
available automated 3D segmentation for spontaneous intracerebral hemorrhage (ICH) …

Intracerebral hemorrhage is the subtype of stroke with the highest mortality rate, especially
when it also causes secondary intraventricular hemorrhage. The optimal surgical option for …

Reduction in CSF volume from baseline to follow-up CT at or beyond 24-hs can serve as a
quantitative biomarker of cerebral edema after stroke. We have demonstrated that …