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 …

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 …

Background A deep learning (DL) model based on representative biopsy tissues can predict
the recurrence and overall survival of patients with glioma, leading to optimized …

Breast cancer has the highest incidence and death rate among women; moreover, its
metastasis to other organs increases the mortality rate. Since several studies have reported …

Objective The alternative extension of the telomeres (ALT) mechanism is activated in lower
grade glioma (LGG), but the role of the ALT mechanism has not been well discussed. The …

Motivation The increasing availability of high-throughput omics data allows for considering a
new medicine centered on individual patients. Precision medicine relies on exploiting these …

Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic
histology characteristics cannot accurately reflect the authentic biological behaviors, clinical …

Simple Summary The estimation of the prognosis of low-grade glioma (LGG) patients using
deep learning models and gene expression data has been intensively studied in recent …