Convolutional neural network techniques for brain tumor classification (from 2015 to 2022): Review, challenges, and future perspectives

Y ** review
S Kierner, J Kucharski, Z Kierner - Journal of Biomedical Informatics, 2023 - Elsevier
Background As the application of Artificial Intelligence (AI) technologies increases in the
healthcare sector, the industry faces a need to combine medical knowledge, often …

PSOWNNs‐CNN: A Computational Radiology for Breast Cancer Diagnosis Improvement Based on Image Processing Using Machine Learning Methods

A Nomani, Y Ansari, MH Nasirpour… - Computational …, 2022 - Wiley Online Library
Early diagnosis of breast cancer is an important component of breast cancer therapy. A
variety of diagnostic platforms can provide valuable information regarding breast cancer …

Machine learning methods for intrusive detection of wormhole attack in mobile ad hoc network (MANET)

M Abdan, SAH Seno - Wireless Communications and Mobile …, 2022 - Wiley Online Library
A wormhole attack is a type of attack on the network layer that reflects routing protocols. The
classification is performed with several methods of machine learning consisting of K‐nearest …

A Novel Highway Routing Protocol in Vehicular Ad Hoc Networks Using VMaSC‐LTE and DBA‐MAC Protocols

E Khezri, E Zeinali, H Sargolzaey - … communications and mobile …, 2022 - Wiley Online Library
The vehicular ad hoc networks (VANETs) are an example of mobile networks, which utilizes
dedicated short‐range communication (DSRC) to establish a wireless connection between …

[Retracted] CT‐ML: Diagnosis of Breast Cancer Based on Ultrasound Images and Time‐Dependent Feature Extraction Methods Using Contourlet Transformation and …

B Hajipour Khire Masjidi, S Bahmani… - Computational …, 2022 - Wiley Online Library
Breast diseases are a group of diseases that appear in different forms. An entire group of
these diseases is breast cancer. This disease is one of the most important and common …

FDCNet: Presentation of the fuzzy CNN and fractal feature extraction for detection and classification of tumors

S Molaei, N Ghorbani, F Dashtiahangar… - Computational …, 2022 - Wiley Online Library
The detection of brain tumors using magnetic resonance imaging is currently one of the
biggest challenges in artificial intelligence and medical engineering. It is important to identify …

[HTML][HTML] Designing a system for battery thermal management: Cooling LIBs by nano-encapsulated phase change material

Y Cao, IB Mansir, A Mouldi, F Aouaini… - Case Studies in Thermal …, 2022 - Elsevier
This study has designed and employed computational fluid dynamics to cool lithium-ion
batteries (LIBs) to keep the temperature constant between 35 and 45° C. A duct was …

MAENet: A novel multi-head association attention enhancement network for completing intra-modal interaction in image captioning

N Hu, C Fan, Y Ming, F Feng - Neurocomputing, 2023 - Elsevier
Image captioning attracts much attention as it bridges computer vision and natural language
processing. Recent works show that transformer-based models with the multi-head self …

Classification of Brain Tumor based on Machine Learning Algorithms: A Review

O Azeez, A Abdulazeez - Journal of Applied Science and Technology …, 2025 - jastt.org
Brain tumor classification using machine learning algorithms is pivotal for medical
diagnostics, particularly in magnetic resonance imaging (MRI) analysis. This review …