Background A decision tree is a crucial tool for describing the factors related to
cardiovascular disease (CVD) risk and for predicting and explaining it for patients. Notably …

Class imbalance is a classical problem in data mining, where the classes in a dataset have
a disproportionate number of instances. Most machine learning tasks fail to work properly …

Microarray gene expression data contain an unbalanced distribution of data samples among
different classes, which poses a challenge to machine learning-based cancer diagnosis. In …

Reasoning task is necessary for scientific work. We proposed a method to ascertained
association rules from a reasoning framework for rule reasoning tasks. The proposed …

The core algorithms of data mining (DM) enable the discovery of new information and
insights by analyzing large amounts of data. Association rules mining (ARM), one of the …

Breast cancer is a highly lethal form of cancer that affects the cells in the breasts and is
second only to lung cancer in terms of its impact on women's health. It is a prevalent type of …

Currently, there are issues of sample imbalance and insufficient sample quantity in graph-
based Alzheimer's disease prediction methods. This can lead to classifiers being biased …

There are several cancer detection methods with their own disadvantages in flexibility, non-
linear complexity and sensitive in imbalance data. In this paper, a new fuzzy bio-inspired …

Lung cancer is the most common type of cancer among males worldwide. It accounts for one
of every five cancer-related fatalities and is prevalent in people aged 55 to 65. Detecting …

Adversarial examples (AE) are used to fool classifier recently, which poses great challenges
for classifier design. Therefore, it is theoretically crucial to evaluate the robustness of …