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Facial Point Graphs for Stroke Identification
Stroke can cause significant damage to neurons, resulting in various sequelae that negatively impact the patient’s ability to perform essential daily...
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Machine Learning Based Stroke Segmentation and Classification from CT-Scan: A Survey
Brain stroke is a life-threatening condition that requires early diagnosis to reduce permanent disability and death. The Computed Tomography (CT)...
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Artificial intelligence in cerebral stroke images classification and segmentation: A comprehensive study
A brain stroke, commonly called as a cerebral vascular accident (CVA) is one of the deadliest diseases across the globe and may lead to various...
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TeleStroke: real-time stroke detection with federated learning and YOLOv8 on edge devices
Stroke, a life-threatening medical condition, necessitates immediate intervention for optimal outcomes. Timely diagnosis and treatment play a crucial...
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Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement
A stroke occurs when an artery in the brain ruptures and bleeds or when the blood supply to the brain is cut off. Blood and oxygen cannot reach the...
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Automated approach to predict cerebral stroke based on fuzzy inference and convolutional neural network
Cerebral stroke indicates a neurological impairment caused by a localized injury to the central nervous system resulting from a diminished blood...
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Development of a flexible self-calculation scoring model to determine stroke occurrence
Stroke has become a significant threat to global public health, the ideal solution to which is primary prevention. Identification and management of...
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Efficient Ensemble Learning Based CatBoost Approach for Early-Stage Stroke Risk Prediction
A stroke is a medical disorder in which the blood arteries in the brain rupture, resulting in a loss of consciousness. When the brain’s blood and...
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Brain stroke prediction model based on boosting and stacking ensemble approach
The concern of brain stroke increases rapidly in young age groups daily. The leading causes of death from stroke globally will rise to 6.7 million...
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Virtual Reality-Based Rehabilitation for Patients with Stroke: Preliminary Results on User Experience
Stroke is one of the major causes of disability worldwide, and most stroke survivors require rehabilitation to recover motor and cognitive functions....
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A robust ischemic stroke lesion segmentation technique using two-pathway 3D deep neural network in MR images
Ischemic stroke is one of the major causes of disability and death of humans. It is a most common disease in aged people which may lead to long-term...
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Assessing the effectiveness of virtual reality serious games in post-stroke rehabilitation: a novel evaluation method
This paper presents a novel evaluation method for assessing the effectiveness of virtual reality serious games (In our work, we used virtual reality...
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A Survey of Stroke Image Analysis Techniques
Stroke is one of the instantaneously shocking and spiking cerebrovascular diseases having substantial residual effects. Image analysis techniques...
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Stroke detection in the brain using MRI and deep learning models
When it comes to finding solutions to issues, deep learning models are pretty much everywhere. Medical image data is best analysed using models based...
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Brain Stroke Prediction Using the Artificial Intelligence
The brain stroke was caused by the stress of the job and the quick pace of life. The most frequent cause of morality in this time period is stroke....
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Development of a novel deep convolutional neural network model for early detection of brain stroke using ct scan images
In recent years, deep convolutional neural network (DCNN) models have shown great promise in the automated detection of brain stroke from CT scan...
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Transparently Predicting Therapy Compliance of Young Adults Following Ischemic Stroke
For stroke rehabilitation, therapy adherence is crucial to maximise patients’ recovery and stimulate re-engagement with normal daily activities....
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Stroke Outcome and Evolution Prediction from CT Brain Using a Spatiotemporal Diffusion Autoencoder
Stroke is a major cause of death and disability worldwide. Accurate outcome and evolution prediction has the potential to revolutionize stroke care...
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An exploration enhanced dynamic arithmetic optimization based modified fuzzy clustering framework for ischemic stroke lesion segmentation
A threatening condition which blocks blood carrying arteries in brain is stroke. Automation algorithms which extract out stroke lesions from whole...
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MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation
The accurate segmentation of stroke lesion regions holds immense significance in sha** treatment strategies and rehabilitation protocols. Due to...