Improving hepatocellular carcinoma diagnosis using an ensemble classification approach based on Harris Hawks Optimization.

Hepato-Cellular Carcinoma (HCC) is the most common type of liver cancer that often occurs in people with chronic liver diseases such as cirrhosis. Although HCC is known as a fatal disease, early detection can lead to successful treatment and improve survival chances. In recent years, the development of computer recognition systems using machine learning approaches has been emphasized by researchers.

Automatic breast cancer diagnosis based on hybrid dimensionality reduction technique and ensemble classification.

Introduction: Feature selection in the face of high-dimensional data can reduce overfitting and learning time, and at the same time improve the accuracy and efficiency of the system. Since there are many irrelevant and redundant features in breast cancer diagnosis, removing such features leads to more accurate prediction and reduced decision time when dealing with large-scale data. Meanwhile, ensemble classifiers are powerful techniques to improve the prediction performance of classification models, where several individual classifier models are combined to achieve higher accuracy.

A fuzzy delay-bandwidth guaranteed routing algorithm for video conferencing services over SDN networks.

Video conferencing is one of the advanced technologies for users that allows online communication despite long distances. High quality communication and ongoing support for the principles of video conferencing service that can be achieved through Software-Defined Networking (SDN). SDN is a new architecture for computer networks that separates the control plane from the data plane to improve network resources and reduce operating costs.