Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

Breast cancer is the most lethal type of cancer for all women worldwide. At the moment,
there are no effective techniques for preventing or curing breast cancer, as the source of the …

Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …

Carcinoma is a primary source of morbidity in women globally, with metastatic disease
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …

In recent decades, microarray datasets have played an important role in triple negative
breast cancer (TNBC) detection. Microarray data classification is a challenging process due …

Accurate detection and classification of breast cancer is a critical task in medical imaging
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …

Diseases is an unusual circumstance that affects single or more parts of a human's body.
Because of lifestyle and patrimonial, different kinds of disease are increasing day by day …

The estimation of the loss and prediction of the casualties in earthquake-stricken areas are
vital for making rapid and accurate decisions during rescue efforts. The number of casualties …

Background Machine learning (ML) has become a vital part of medical imaging research.
ML methods have evolved over the years from manual seeded inputs to automatic …