Benjamin Brush
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View article: Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke
Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke Open
In treating malignant cerebral edema after a large middle cerebral artery stroke, clinicians need quantitative tools for real-time risk assessment. Existing predictive models typically estimate risk at one, early time point, failing to acc…
View article: Later midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke
Later midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke Open
View article: HELMET: A Hybrid Machine Learning Framework for Real-Time Prediction of Edema Trajectory in Large Middle Cerebral Artery Stroke
HELMET: A Hybrid Machine Learning Framework for Real-Time Prediction of Edema Trajectory in Large Middle Cerebral Artery Stroke Open
Malignant cerebral edema occurs when brain swelling displaces and compresses vital midline structures within the first week of a large middle cerebral artery stroke. Early interventions such as hyperosmolar therapy or surgical decompressio…
View article: Association of Dynamic Trajectories of Time-Series Data and Life-Threatening Mass Effect in Large Middle Cerebral Artery Stroke
Association of Dynamic Trajectories of Time-Series Data and Life-Threatening Mass Effect in Large Middle Cerebral Artery Stroke Open
View article: Association of large core middle cerebral artery stroke and hemorrhagic transformation with hospitalization outcomes
Association of large core middle cerebral artery stroke and hemorrhagic transformation with hospitalization outcomes Open
Historically, investigators have not differentiated between patients with and without hemorrhagic transformation ( HT ) in large core ischemic stroke at risk for life-threatening mass effect ( LTME ) from cerebral edema. Our objective was …
View article: Later Midline Shift Is Associated with Better Outcomes after Large Middle Cerebral Artery Stroke
Later Midline Shift Is Associated with Better Outcomes after Large Middle Cerebral Artery Stroke Open
Background/Objective Space occupying cerebral edema is the most feared early complication after large ischemic stroke, occurring in up to 30% of patients with middle cerebral artery (MCA) occlusion, and is reported to peak 2-4 days after i…
View article: Follow-up ASPECTS improves prediction of potentially lethal malignant edema in patients with large middle cerebral artery stroke
Follow-up ASPECTS improves prediction of potentially lethal malignant edema in patients with large middle cerebral artery stroke Open
Background Recent studies have shown that follow-up head CT is a strong predictor of functional outcomes in patients with middle cerebral artery stroke and mechanical thrombectomy. We sought to determine whether total and/or regional follo…
View article: Dynamic trajectories of life-threatening mass effect in patients with large middle cerebral artery stroke
Dynamic trajectories of life-threatening mass effect in patients with large middle cerebral artery stroke Open
Background Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery ( MCA ) stroke. Little is known about longitudinal trajectori…
View article: Natural Language Processing of Radiology Reports to Detect Complications of Ischemic Stroke
Natural Language Processing of Radiology Reports to Detect Complications of Ischemic Stroke Open
View article: Abstract 1122‐000089: Characterization of Critical Sequelae in Ischemic Stroke Using Natural Language Processing
Abstract 1122‐000089: Characterization of Critical Sequelae in Ischemic Stroke Using Natural Language Processing Open
Introduction : Automated processing of electronic health data to classify complications of ischemic stroke serves numerous purposes, including improved electronic phenotyping for clinical research. Here, we present a natural language proce…