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

Simple Summary Graph Neural Networks are emerging as a powerful tool for structured data
analysis, and predictive modeling in massive multimodal datasets. In this review, we survey …

The identification of cancer driver genes (CDGs) poses challenges due to the intricate
interdependencies among genes and the influence of measurement errors and noise. We …

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies,
given its significant impact on global mortality and morbidity. Here, we propose a novel deep …

The application of machine learning (ML) methods to analyze changes in gene expression
patterns has recently emerged as a powerful approach in cancer research, enhancing our …

Cancer is a complex disease driven by mutations in the genes that play critical roles in
cellular processes. The identification of cancer driver genes is crucial for understanding …

Identifying the grade of Gastrodia elata in the market has low efficiency and accuracy. To
address this issue, an I-YOLOX object detection algorithm based on deep learning and …

Cancer development is closely linked to the accumulation of mutations in driver genes.
Therefore, identification of driver genes is crucial for understanding the molecular basis of …

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies,
given its significant impact on global mortality and morbidity. Here, we propose a novel deep …

The emergence and rapid development of deep learning, specifically transformer-based
architectures and attention mechanisms, have had transformative implications across …