Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

In the era of healthcare and its related research fields, the dimensionality problem of high-
dimensional data is a massive challenge as it is crucial to identify significant genes while …

Gene expression datasets offer a wide range of information about various biological
processes. However, it is difficult to find the important genes among the high-dimensional …

The data-driven modern era has enabled the collection of large amounts of biomedical and
clinical data. DNA microarray gene expression datasets have mainly gained significant …

Accurate classification of high-dimensional biomedical data highly depends on the efficient
recognition of the data's main features which can be used to assist diagnose related …

Disease diagnosis and prediction methods in biotechnology and medicine have significantly
advanced over time. Consequently, analyzing raw gene expression is crucial for identifying …

For breast cancer diagnosis, computer-aided classification of histopathological images is of
critical importance for correct and early diagnosis. Transfer learning approaches for feature …

Cancer prediction in the early stage is a topic of major interest in medicine since it allows
accurate and efficient actions for successful medical treatments of cancer. Mostly cancer …

The design of an optimal framework for the prediction of cancer from high-dimensional and
imbalanced microarray data is a challenging job in the fields of bioinformatics and machine …

Detecting tumors using gene analysis in microarray data is a critical area of research in
artificial intelligence and bioinformatics. However, due to the large number of genes …