The early diagnosis of cancer, as one of the major causes of death, is vital for cancerous
patients. Diagnosing diseases in general and cancer in particular is a considerable …

With the development of artificial intelligence, big data classification technology provides the
advantageous help for the medicine auxiliary diagnosis research. While due to the different …

An important problem in medical data analysis is imbalance dataset. This problem is a
cause of diagnostic mistake. The results of diagnostic affect to life of patients. If a doctor fails …

The problem of imbalanced data classification often exists in medical diagnosis. Traditional
classification algorithms usually assume that the number of samples in each class is similar …

Nowadays, healthcare is the prime need of every human being in the world, and clinical
datasets play an important role in developing an intelligent healthcare system for monitoring …

A considerable amount of health record (HR) data has been stored due to recent advances
in the digitalization of medical systems. However, it is not always easy to analyze HR data …

Most classification algorithms assume that classes are in a balanced state. However,
datasets with class imbalances are everywhere. The classes of actual medical datasets are …

In recent decades, machine learning algorithms have been used in different fields; one of
the most used fields is the health sector. Biomedical data are usually extensive in size, and …

Real-world datasets in many domains like medical, intrusion detection, fraud transactions
and bioinformatics are highly imbalanced. In classification problems, imbalanced datasets …

Nowadays, handling of the imbalance data is a major challenge. Imbalanced data set
means the instances of one class are much more than the instances of another class where …