Machine learning for brain stroke: a review
Abstract Machine Learning (ML) delivers an accurate and quick prediction outcome and it
has become a powerful tool in health settings, offering personalized clinical care for stroke …
has become a powerful tool in health settings, offering personalized clinical care for stroke …
[HTML][HTML] Machine learning in action: stroke diagnosis and outcome prediction
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …
In stroke, commercially available machine learning algorithms have already been …
[HTML][HTML] Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a scoping review
C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …
human intelligence using machines so that such machines gain problem-solving and …
[HTML][HTML] A review on computer aided diagnosis of acute brain stroke
Amongst the most common causes of death globally, stroke is one of top three affecting over
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
100 million people worldwide annually. There are two classes of stroke, namely ischemic …
Predicting treatment-specific lesion outcomes in acute ischemic stroke from 4D CT perfusion imaging using spatio-temporal convolutional neural networks
For the diagnosis and precise treatment of acute ischemic stroke, predicting the final location
and volume of lesions is of great clinical interest. Current deep learning-based prediction …
and volume of lesions is of great clinical interest. Current deep learning-based prediction …
Artificial intelligence for clinical decision support in acute ischemic stroke: A systematic review
Background: Established randomized trial-based parameters for acute ischemic stroke
group patients into generic treatment groups, leading to attempts using various artificial …
group patients into generic treatment groups, leading to attempts using various artificial …
[HTML][HTML] The predictive performance of artificial intelligence on the outcome of stroke: a systematic review and meta-analysis
Y Yang, L Tang, Y Deng, X Li, A Luo, Z Zhang… - Frontiers in …, 2023 - frontiersin.org
Objectives This study aimed to assess the accuracy of artificial intelligence (AI) models in
predicting the prognosis of stroke. Methods We searched PubMed, Embase, and Web of …
predicting the prognosis of stroke. Methods We searched PubMed, Embase, and Web of …
[HTML][HTML] Attention-Based Fusion of Ultrashort Voice Utterances and Depth Videos for Multimodal Person Identification
Multimodal deep learning, in the context of biometrics, encounters significant challenges
due to the dependence on long speech utterances and RGB images, which are often …
due to the dependence on long speech utterances and RGB images, which are often …
CNN-LSTM based multimodal MRI and clinical data fusion for predicting functional outcome in stroke patients
N Hatami, TH Cho, L Mechtouff, OF Eker… - 2022 44th Annual …, 2022 - ieeexplore.ieee.org
Clinical outcome prediction plays an important role in stroke patient management. From a
machine learning point-of-view, one of the main challenges is dealing with heterogeneous …
machine learning point-of-view, one of the main challenges is dealing with heterogeneous …
Transfer learning-based classification comparison of stroke
RAJ Alhatemi, S Savaş - Computer Science, 2022 - dergipark.org.tr
One type of brain disease that significantly harms people's lives and health is stroke. The
diagnosis and management of strokes both heavily rely on the quantitative analysis of brain …
diagnosis and management of strokes both heavily rely on the quantitative analysis of brain …