Vision Transformers in medical computer vision—A contemplative retrospection

A Parvaiz, MA Khalid, R Zafar, H Ameer, M Ali… - … Applications of Artificial …, 2023 - Elsevier
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

Brain tumor detection and classification using intelligence techniques: an overview

S Solanki, UP Singh, SS Chouhan, S Jain - IEEE Access, 2023 - ieeexplore.ieee.org
A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …

An effective approach to detect and identify brain tumors using transfer learning

N Ullah, JA Khan, MS Khan, W Khan, I Hassan… - Applied Sciences, 2022 - mdpi.com
Brain tumors are considered one of the most serious, prominent and life-threatening
diseases globally. Brain tumors cause thousands of deaths every year around the globe …

Crossover smell agent optimized multilayer perceptron for precise brain tumor classification on MRI images

M Arumugam, A Thiyagarajan, L Adhi… - Expert Systems with …, 2024 - Elsevier
The Brain tumor is considered an unusual growth of cells in the nervous system that restricts
the normal functionality of the brain. However, is generated in the skull and pressures the …

A robust end-to-end deep learning-based approach for effective and reliable BTD using MR images

N Ullah, MS Khan, JA Khan, A Choi, MS Anwar - Sensors, 2022 - mdpi.com
Detection of a brain tumor in the early stages is critical for clinical practice and survival rate.
Brain tumors arise in multiple shapes, sizes, and features with various treatment options …

Explainable Deep Learning Approach for Multi-Class Brain Magnetic Resonance Imaging Tumor Classification and Localization Using Gradient-Weighted Class …

T Hussain, H Shouno - Information, 2023 - mdpi.com
Brain tumors (BT) present a considerable global health concern because of their high
mortality rates across diverse age groups. A delay in diagnosing BT can lead to death …

HRIDM: Hybrid Residual/Inception-Based Deeper Model for Arrhythmia Detection from Large Sets of 12-Lead ECG Recordings

SA Moqurrab, HM Rai, J Yoo - Algorithms, 2024 - search.proquest.com
Heart diseases such as cardiovascular and myocardial infarction are the foremost reasons
of death in the world. The timely, accurate, and effective prediction of heart diseases is …

A novel hybrid ensemble based Alzheimer's identification system using deep learning technique

I Ayus, D Gupta - Biomedical Signal Processing and Control, 2024 - Elsevier
Alzheimer's disease (AD) is an irreversible neurological degenerative disorder
characterized by the deterioration of brain cells resulting in cognitive impairment. There is a …

Optimizing CNN based model for thyroid nodule classification using data augmentation, segmentation and boundary detection techniques

R Srivastava, P Kumar - Multimedia Tools and Applications, 2023 - Springer
Thyroid nodule is an asymptomatic disorder which mostly occurs due to high production of
thyroid hormones from the thyroid gland. The diagnosis is usually made by the radiologist …

[PDF][PDF] Detection and classification of MRI brain tumors using S3-DRLSTM based deep learning model

E Aarthi, S Jana, WG Theresa… - … Journal of Electrical …, 2022 - ijeer.forexjournal.co.in
░ ABSTRACT-Develo** an automated brain tumor diagnosis system is a highly
challenging task in current days, due to the complex structure of nervous system. The …