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 …

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review

B Jena, S Saxena, GK Nayak, L Saba, N Sharma… - Computers in Biology …, 2021 - Elsevier
Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …

Transfer learning for medical images analyses: A survey

X Yu, J Wang, QQ Hong, R Teku, SH Wang, YD Zhang - Neurocomputing, 2022 - Elsevier
The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review

A Shoeibi, M Khodatars, M Jafari, P Moridian… - Computers in Biology …, 2021 - Elsevier
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Early diagnosis of brain tumour mri images using hybrid techniques between deep and machine learning

EM Senan, ME Jadhav, TH Rassem… - … Methods in Medicine, 2022 - Wiley Online Library
Cancer is considered one of the most aggressive and destructive diseases that shortens the
average lives of patients. Misdiagnosed brain tumours lead to false medical intervention …

Dry bean cultivars classification using deep cnn features and salp swarm algorithm based extreme learning machine

M Dogan, YS Taspinar, I Cinar, R Kursun… - … and Electronics in …, 2023 - Elsevier
Since dry bean varieties have different qualities and economic values, their separation is of
great importance in the field of agriculture. In recent years, the use of artificial intelligence …

Popular deep learning algorithms for disease prediction: a review

Z Yu, K Wang, Z Wan, S Xie, Z Lv - Cluster Computing, 2023 - Springer
Due to its automatic feature learning ability and high performance, deep learning has
gradually become the mainstream of artificial intelligence in recent years, playing a role in …

Deep learning (CNN) and transfer learning: a review

J Gupta, S Pathak, G Kumar - Journal of Physics: Conference …, 2022 - iopscience.iop.org
Deep Learning is a machine learning area that has recently been used in a variety of
industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the …

Pre-trained deep learning models for brain MRI image classification

S Krishnapriya, Y Karuna - Frontiers in Human Neuroscience, 2023 - frontiersin.org
Brain tumors are serious conditions caused by uncontrolled and abnormal cell division.
Tumors can have devastating implications if not accurately and promptly detected. Magnetic …

Brain tumor categorization from imbalanced MRI dataset using weighted loss and deep feature fusion

S Deepak, PM Ameer - Neurocomputing, 2023 - Elsevier
Deep learning-based brain tumor classification from brain magnetic resonance imaging
(MRI) is a significant research problem. The research problem encounters a major …