AIMC Topic: Subarachnoid Hemorrhage

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Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Sensors (Basel, Switzerland) Jul 14, 2024
Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA is the bulging of a blood vessel caused by a weakening of its wall. This bulge can rupture and, in most cases, cause internal bleeding. In most cases,...
Humans Image Processing, Computer-Assisted Subarachnoid Hemorrhage Intracranial Aneurysm Neural Networks, Computer Algorithms Deep Learning
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Machine learning predicts cerebral vasospasm in patients with subarachnoid haemorrhage.

EBioMedicine Jun 19, 2024
BACKGROUND: Cerebral vasospasm (CV) is a feared complication which occurs after 20-40% of subarachnoid haemorrhage (SAH). It is standard practice to admit patients with SAH to intensive care for an extended period of resource-intensive monitoring. We...
Vasospasm, Intracranial Verapamil Prognosis Middle Aged Intensive Care Units ROC Curve Female Subarachnoid Hemorrhage Aged Adult Male Humans Machine Learning
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Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study.

BMC neurology May 27, 2024
BACKGROUND: Early prediction of delayed cerebral ischemia (DCI) is critical to improving the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). Machine learning (ML) algorithms can learn from intricate information unbiasedly and facilitate the e...
Middle Aged China Cohort Studies Aged Adult Male Subarachnoid Hemorrhage Brain Ischemia Humans Machine Learning Prognosis Retrospective Studies Female
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Evaluating Deep Learning Techniques for Detecting Aneurysmal Subarachnoid Hemorrhage: A Comparative Analysis of Convolutional Neural Network and Transfer Learning Models.

World neurosurgery May 6, 2024
OBJECTIVE: Machine learning and deep learning techniques offer a promising multidisciplinary solution for subarachnoid hemorrhage (SAH) detection. The novel transfer learning approach mitigates the time constraints associated with the traditional tec...
Neural Networks, Computer Female Male Humans Intracranial Aneurysm Middle Aged Deep Learning Subarachnoid Hemorrhage
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Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

Journal of neurosurgery Mar 29, 2024
OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently devel...
Female Aged Adult Male Middle Aged Postoperative Complications Humans Retrospective Studies Tomography, X-Ray Computed Deep Learning Hydrocephalus Subarachnoid Hemorrhage
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Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data.

Journal of clinical monitoring and computing Mar 21, 2024
Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic congestion. Treatment of this acute condition often includes establishing an external ventricular drainage (EVD). However, chronic hydrocephalus develops...
Ventriculoperitoneal Shunt Hydrocephalus Subarachnoid Hemorrhage Critical Care Middle Aged ROC Curve Retrospective Studies Humans Intensive Care Units Neural Networks, Computer Female Aged Machine Learning Adult Male
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Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis.

Neurocritical care Sep 5, 2023
Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary method to predict DCI, but it has low accuracy. This study assessed whether other machine learning (ML) m...
Sensitivity and Specificity Subarachnoid Hemorrhage Brain Ischemia Humans Machine Learning Algorithms
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Deep learning-assisted identification and quantification of aneurysmal subarachnoid hemorrhage in non-contrast CT scans: Development and external validation of Hybrid 2D/3D UNet.

NeuroImage Aug 11, 2023
Accurate stroke assessment and consequent favorable clinical outcomes rely on the early identification and quantification of aneurysmal subarachnoid hemorrhage (aSAH) in non-contrast computed tomography (NCCT) images. However, hemorrhagic lesions can...
Humans Tomography, X-Ray Computed Deep Learning Contrast Media Stroke Subarachnoid Hemorrhage
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A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Progress in biophysics and molecular biology Jul 25, 2023
The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, how...
Subarachnoid Hemorrhage Humans Aneurysm, Ruptured Artificial Intelligence Intracranial Aneurysm Machine Learning Reproducibility of Results Deep Learning
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Development and External Validation of a Deep Learning Algorithm to Identify and Localize Subarachnoid Hemorrhage on CT Scans.

Neurology Jan 13, 2023
BACKGROUND AND OBJECTIVES: In medical imaging, a limited number of trained deep learning algorithms have been externally validated and released publicly. We hypothesized that a deep learning algorithm can be trained to identify and localize subarachn...
Head Tomography, X-Ray Computed Humans Deep Learning Subarachnoid Hemorrhage Algorithms
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