Simple Summary The rapidly advancing field of deep learning, specifically transformer-
based architectures and attention mechanisms, has found substantial applicability in …

Simple Summary The ongoing advancements in deep learning, notably its use in predicting
cancer survival through genomic data analysis, calls for an up-to-date review. This paper …

An evaluation of the expression and predictive significance of the MDM2 gene in brain lower-
grade glioma (LGG) cancer was carried out using onco-informatics pipelines. Several …

Selecting the most suitable activation function is a critical factor in the effectiveness of deep
learning models, as it influences their learning capacity, stability, and computational …

Selecting the most suitable activation function is a critical factor in the effectiveness of deep
learning models, as it influences their learning capacity, stability, and computational …

With the increasing incidence of breast cancer, accurate prognosis prediction of breast
cancer patients is a key issue in current cancer research, and it is also of great significance …

As the field of deep learning experiences a meteoric rise, the urgency to decipher the
complex geometric properties of feature spaces, which underlie the effectiveness of diverse …

This review paper provides an extensive analysis of the rapidly evolving convergence of
deep learning and long non-coding RNAs (lncRNAs). Considering the recent advancements …

Convolutional Neural Networks (CNNs) have demonstrated remarkable performance in
medical image segmentation tasks, with the U-Net architecture being a prominent example …

Predicting the likelihood of survival is of paramount importance for individuals diagnosed
with cancer as it provides invaluable information regarding prognosis at an early stage. This …