Deep learning guided stroke management: a review of clinical applications
R Feng, M Badgeley, J Mocco… - Journal of …, 2018 - jnis.bmj.com
Stroke is a leading cause of long-term disability, and outcome is directly related to timely
intervention. Not all patients benefit from rapid intervention, however. Thus a significant …
intervention. Not all patients benefit from rapid intervention, however. Thus a significant …
[HTML][HTML] Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution …
Over the last 15 years, basic thresholding techniques in combination with standard statistical
correlation-based data analysis tools have been widely used to investigate different aspects …
correlation-based data analysis tools have been widely used to investigate different aspects …
Prediction of tissue outcome and assessment of treatment effect in acute ischemic stroke using deep learning
Background and Purpose—Treatment options for patients with acute ischemic stroke
depend on the volume of salvageable tissue. This volume assessment is currently based on …
depend on the volume of salvageable tissue. This volume assessment is currently based on …
AI-based stroke disease prediction system using real-time electromyography signals
Stroke is a leading cause of disabilities in adults and the elderly which can result in
numerous social or economic difficulties. If left untreated, stroke can lead to death. In most …
numerous social or economic difficulties. If left untreated, stroke can lead to death. In most …
MR images, brain lesions, and deep learning
D Castillo, V Lakshminarayanan… - Applied Sciences, 2021 - mdpi.com
Featured Application This review provides a critical review of deep/machine learning
algorithms used in the identification of ischemic stroke and demyelinating brain diseases. It …
algorithms used in the identification of ischemic stroke and demyelinating brain diseases. It …
Merging current health care trends: innovative perspective in aging care
MÁ Gandarillas, N Goswami - Clinical interventions in aging, 2018 - Taylor & Francis
Current trends in health care delivery and management such as predictive and personalized
health care incorporating information and communication technologies, home-based care …
health care incorporating information and communication technologies, home-based care …
Deep learning of tissue fate features in acute ischemic stroke
In acute ischemic stroke treatment, prediction of tissue survival outcome plays a fundamental
role in the clinical decision-making process, as it can be used to assess the balance of risk …
role in the clinical decision-making process, as it can be used to assess the balance of risk …
Application of machine learning techniques for characterization of ischemic stroke with MRI images: a review
Magnetic resonance imaging (MRI) is a standard tool for the diagnosis of stroke, but its
manual interpretation by experts is arduous and time-consuming. Thus, there is a need for …
manual interpretation by experts is arduous and time-consuming. Thus, there is a need for …
Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA
The accurate identification of irreversible infarction and salvageable tissue is important in
planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic …
planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic …
A multi-scale approach for detection of ischemic stroke from brain MR images using discrete curvelet transformation
Among the various brain diseases, ischemic stroke is considered to be a major cause
behind death and disability in the developed countries. The segmentation of lesion serves to …
behind death and disability in the developed countries. The segmentation of lesion serves to …