For the last two decades, oversampling has been employed to overcome the challenge of
learning from imbalanced datasets. Many approaches to solving this challenge have been …

In today's digital world, information is growing along with the expansion of Internet usage
worldwide. As a consequence, bulk of data is generated constantly which is known to be …

Brain tumors are most common in children and the elderly. It is a serious form of cancer
caused by uncontrollable brain cell growth inside the skull. Tumor cells are notoriously …

The brain is the most vital component of the neurological system. Therefore, brain tumor
classification is a very challenging task in the field of medical image analysis. There has …

Deep learning has surged in popularity in recent years, notably in the domains of medical
image processing, medical image analysis, and bioinformatics. In this study, we offer a …

Cancer of the brain is most common in the elderly and young and can be fatal in both. Brain
tumours can heal better if they are diagnosed and treated quickly. When it comes to …

Biomedical image processing is a hot research topic which helps to majorly assist the
disease diagnostic process. At the same time, breast cancer becomes the deadliest disease …

The hybrid parallel fuzzy convolutional neural network (HP-FCNN) is a ground-breaking
method for medical image analysis that combines the interpretive capacity of fuzzy logic with …

Since most classifiers are biased toward the dominant class, class imbalance is a
challenging problem in machine learning. The most popular approaches to solving this …

Big data is quickly becoming a new area where administrative work can be improved. Even
so, it is still in the early stages of being used in hospitals in countries with less technology …