This paper discusses the problem of detecting cancer using such biomarkers as blood
protein markers. The purpose of this research is to propose an approach for making …

This paper deals with the problem of diagnosing oncological diseases based on blood
protein markers. The goal of the study is to develop a novel approach in decision-making on …

In this study, we propose to use a method based on the combination of sample entropy with
multiscale and multidimensional approaches, along with a fuzzy function. The model was …

The explosive growth of data in volume, velocity and diversity that are produced by medical
applications has contributed to abundance of big data. Current solutions for efficient data …

Proper tuning of hyper-parameters is essential to the successful application of SVM-
classifiers. Several methods have been used for this problem: grid search, random search …

In this study, feature selection in classification based problems is highlighted. The role of
feature selection methods is to select important features by discarding redundant and …

In this work an entropic filtering algorithm (EFA) for feature selection is described, as a
workable method to generate a relevant subset of genes. This is a fast feature selection …

A clinical decision support system is a computer-based system that is designed to assist
healthcare providers with clinical decision-making by analyzing electronic health records …

Although medical data classification is a challenging task, it allures the research community
so that it can help to take precise precautions in restraining future diseases. To perpetrate …

Advances in the gene sequencing technology and the outbreak of artificial intelligence have
made precision medicine a reality recently. Applying machine learning algorithms to cancer …