AIMC Topic: Brain Edema

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On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

European journal of radiology Jul 20, 2018
PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T-W/FLAIR images. Most studies involving differentiation between vasog...
Young Adult Adult Aged Middle Aged ROC Curve Male Brain Neoplasms Brain Female Retrospective Studies Humans Preoperative Care Diagnosis, Differential Magnetic Resonance Imaging Postoperative Period Brain Edema Glioma Image Processing, Computer-Assisted Support Vector Machine
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Prediction of final infarct volume on subacute MRI by quantifying cerebral edema in ischemic stroke.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism Jan 1, 2016
Final infarct volume in stroke trials is assessed on images obtained between 30 and 90 days after stroke onset. Imaging at such delayed timepoints is problematic because patients may be lost to follow-up or die before the scan. Obtaining an early ass...
Sensitivity and Specificity Predictive Value of Tests Tissue Plasminogen Activator Time Factors Stroke Brain Edema Male Brain Ischemia Cerebral Infarction Models, Biological Humans Female Aged Magnetic Resonance Imaging
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Predicting the efficacy of bevacizumab on peritumoral edema based on imaging features and machine learning.

Scientific reports May 8, 2025
This study proposes a novel approach to predict the efficacy of bevacizumab (BEV) in treating peritumoral edema in metastatic brain tumor patients by integrating advanced machine learning (ML) techniques with comprehensive imaging and clinical data. ...
Bevacizumab Brain Edema Treatment Outcome Brain Neoplasms Retrospective Studies Adult Middle Aged Male Antineoplastic Agents, Immunological Algorithms Magnetic Resonance Imaging Humans Machine Learning Aged Female
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Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.

Brain and behavior Jan 1, 2025
INTRODUCTION: Stroke patients are at high risk of developing cerebral edema, which can have severe consequences. However, there are currently few effective tools for early identification or prediction of this risk. As machine learning (ML) is increas...
Humans Machine Learning Predictive Value of Tests Risk Assessment Stroke Brain Edema
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