Recently, significant efforts have been made to create Health Digital Twins (HDTs), Digital
Twins for clinical applications. Heart modeling is one of the fastest-growing fields, which …

Owing to their superior capabilities and advanced achievements, Transformers have
gradually attracted attention with regard to understanding complex brain processing …

A significant issue in computer-aided diagnosis (CAD) for medical applications is brain
tumor classification. Radiologists could reliably detect tumors using machine learning …

Background The Rotation Invariant Vision Transformer (RViT) is a novel deep learning
model tailored for brain tumor classification using MRI scans. Methods RViT incorporates …

Magnetic Resonance Imaging (MRI) is a critical imaging technique that provides detailed
visualization of internal structures without harmful radiation. This review focuses on key MRI …

Brain tumor classification is a challenging task in medical image analysis. In this paper, we
propose a novel approach to brain tumor classification using a vision transformer with a …

Brain tumor is an anomalous growth of glial and neural cells and is considered as one of the
primary causes of death worldwide. Therefore, it is essential to identify the tumor as soon as …

The advent of artificial intelligence in medical imaging has paved the way for significant
advancements in the diagnosis of brain tumors. This study presents a novel ensemble …

The identification and classification of brain tumors from medical images is a challenging
task, which plays a crucial role in treatment planning. In recent times, the transformer models …

Brain tumors present a significant global health challenge, and their early detection and
accurate classification are crucial for effective treatment strategies. This study presents a …