Multi-feature analysis for automated brain stroke classification using weighted Gaussian naïve Bayes classifier
S Jayachitra, A Prasanth - journal of circuits, systems and …, 2021 - World Scientific
In today's world, brain stroke is considered as a life-threatening disease provoked by
undesirable blockage among the arteries feeding the human brain. The timely diagnosis of …
undesirable blockage among the arteries feeding the human brain. The timely diagnosis of …
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 …
A customized VGG19 network with concatenation of deep and handcrafted features for brain tumor detection
Brain tumor (BT) is one of the brain abnormalities which arises due to various reasons. The
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …
Developing and deploying deep learning models in brain magnetic resonance imaging: A review
K Aggarwal, M Manso Jimeno, KS Ravi… - NMR in …, 2023 - Wiley Online Library
Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to
alleviate the burden on radiologists and MR technologists, and improve throughput. The …
alleviate the burden on radiologists and MR technologists, and improve throughput. The …
An ensemble learning approach for brain cancer detection exploiting radiomic features
Abstract Background and Objective The brain cancer is one of the most aggressive tumour:
the 70% of the patients diagnosed with this malignant cancer will not survive. Early detection …
the 70% of the patients diagnosed with this malignant cancer will not survive. Early detection …
A deep learning approach for detecting stroke from brain CT images using OzNet
A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply
to the brain. After the stroke, the damaged area of the brain will not operate normally. As a …
to the brain. After the stroke, the damaged area of the brain will not operate normally. As a …
Evaluation of brain tumor using brain MRI with modified-moth-flame algorithm and Kapur's thresholding: A study
S Kadry, V Rajinikanth, NSM Raja… - Evolutionary …, 2021 - Springer
Brain abnormality is a severe illness in humans. An unrecognised and untreated brain
illness will lead to a lot of complications despite of gender and age. Brain tumor is one of the …
illness will lead to a lot of complications despite of gender and age. Brain tumor is one of the …
A data constrained approach for brain tumour detection using fused deep features and SVM
The identification of MR images of the brain with tumours is one of the most critical tasks of
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
Adversarial Convolutional Neural Network for Predicting Blood Clot Ischemic Stroke
MA Hambali, PA Agwu - Journal of Computing Theories and …, 2024 - dl.futuretechsci.org
Digital Pathology Image Analysis (DPIA) is one of the areas where deep learning (DL)
techniques offer modern, cutting-edge functionality. Convolutional Neural Network (CNN) …
techniques offer modern, cutting-edge functionality. Convolutional Neural Network (CNN) …
Building trusted startup teams from LinkedIn attributes: A higher order probabilistic analysis
Startups arguably contribute to the current business landscape by developing innovative
products and services. The discovery of business partners and employees with a specific …
products and services. The discovery of business partners and employees with a specific …