Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

QD Buchlak, N Esmaili, JC Leveque, C Bennett… - Journal of Clinical …, 2021 - Elsevier
Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year
survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for …

MRI-based brain tumor classification using ensemble of deep features and machine learning classifiers

J Kang, Z Ullah, J Gwak - Sensors, 2021 - mdpi.com
Brain tumor classification plays an important role in clinical diagnosis and effective
treatment. In this work, we propose a method for brain tumor classification using an …

A hybrid CNN-SVM threshold segmentation approach for tumor detection and classification of MRI brain images

MO Khairandish, M Sharma, V Jain, JM Chatterjee… - Irbm, 2022 - Elsevier
Objective In this research paper, the brain MRI images are going to classify by considering
the excellence of CNN on a public dataset to classify Benign and Malignant tumors …

Deep learning techniques for the classification of brain tumor: A comprehensive survey

A Younis, Q Li, M Khalid, B Clemence… - IEEE Access, 2023 - ieeexplore.ieee.org
Researchers have given immense consideration to unsupervised approaches because of
their tendency for automatic feature generation and excellent performance with a reduced …

Deep CNN for brain tumor classification

W Ayadi, W Elhamzi, I Charfi, M Atri - Neural processing letters, 2021 - Springer
Brain tumor represents one of the most fatal cancers around the world. It is common cancer
in adults and children. It has the lowest survival rate and various types depending on their …

An enhanced deep learning approach for brain cancer MRI images classification using residual networks

SAA Ismael, A Mohammed, H Hefny - Artificial intelligence in medicine, 2020 - Elsevier
Cancer is the second leading cause of death after cardiovascular diseases. Out of all types
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …

A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models

NF Aurna, MA Yousuf, KA Taher, AKM Azad… - Computers in biology and …, 2022 - Elsevier
The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to
the leading cause of cancer related mortality. The treatment procedure of the brain tumor …

Cnn based multiclass brain tumor detection using medical imaging

P Tiwari, B Pant, MM Elarabawy… - Computational …, 2022 - Wiley Online Library
Brain tumors are the 10th leading reason for the death which is common among the adults
and children. On the basis of texture, region, and shape there exists various types of tumor …

Timedistributed-cnn-lstm: A hybrid approach combining cnn and lstm to classify brain tumor on 3d mri scans performing ablation study

S Montaha, S Azam, AKMRH Rafid, MZ Hasan… - IEEE …, 2022 - ieeexplore.ieee.org
Identification of brain tumors at an early stage is crucial in cancer diagnosis, as a timely
diagnosis can increase the chances of survival. Considering the challenges of tumor …

Improving electric energy consumption prediction using CNN and Bi-LSTM

T Le, MT Vo, B Vo, E Hwang, S Rho, SW Baik - Applied Sciences, 2019 - mdpi.com
The electric energy consumption prediction (EECP) is an essential and complex task in
intelligent power management system. EECP plays a significant role in drawing up a …