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Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
Deep learning for neurodegenerative disorder (2016 to 2022): A systematic review
J Chaki, M Woźniak - Biomedical Signal Processing and Control, 2023 - Elsevier
A neurodegenerative disorder, such as Parkinson's, Alzheimer's, epilepsy, stroke, and
others, is a type of disease in which central nervous system cells stop working or die …
others, is a type of disease in which central nervous system cells stop working or die …
[HTML][HTML] An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning
Brain tumors are among the most fatal and devastating diseases, often resulting in
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …
Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm
In the last decade, there has been a significant increase in medical cases involving brain
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi-grade segmentation through hybrid caps-VGGNet model
Around the world, brain tumors are becoming the leading cause of mortality. The inability to
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …
A hybrid deep CNN-Cov-19-Res-Net Transfer learning architype for an enhanced Brain tumor Detection and Classification scheme in medical image processing
The major intention of this work is to detect the Brain tumor with accuracy by reducing error
rate and computational complexity. Therefore, in this manuscript, a Deep Convolutional …
rate and computational complexity. Therefore, in this manuscript, a Deep Convolutional …
[HTML][HTML] An automated metaheuristic-optimized approach for diagnosing and classifying brain tumors based on a convolutional neural network
Brain tumors must be classified to determine their severity and appropriate therapy. Applying
Artificial Intelligence to medical imaging has enabled remarkable developments. The …
Artificial Intelligence to medical imaging has enabled remarkable developments. The …
A comprehensive analysis of recent deep and federated-learning-based methodologies for brain tumor diagnosis
Brain tumors are a deadly disease with a high mortality rate. Early diagnosis of brain tumors
improves treatment, which results in a better survival rate for patients. Artificial intelligence …
improves treatment, which results in a better survival rate for patients. Artificial intelligence …
[PDF][PDF] A systematic literature review of deep and machine learning algorithms in brain tumor and meta-analysis
Brain tumor (BT) is considered one of the dangerous conditions that could strike both adults
and children. 85 to 90% of all primary malignancies of the “Central Nervous System (CNS)” …
and children. 85 to 90% of all primary malignancies of the “Central Nervous System (CNS)” …