In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

In general, the various medical systems currently available provide insights into changes in
the tumor genome of patients with tumor sequencing. Most of the tumor DNA sequencing …

Abstract Background and Objective: Cancer is a complex worldwide health problem
associated with high mortality. With the rapid development of the high-throughput …

Machine learning is one of the most exciting recent technologies in Artificial Intelligence.
Learning algorithms in many applications that's we make use of daily. Every time a web …

In today's world, machine learning has gained much popularity, and its algorithms are
employed in every field such as pattern recognition, object detection, text interpretation and …

Motivation: Cancer diagnosis is one of the most important emerging clinical applications of
gene expression microarray technology. We are seeking to develop a computer system for …

The main aim of this paper is to design and develop an approach for kidney disease
detection and segmentation using a combination of clustering and classification approach …

DNA microarray technology can monitor the expression levels of thousands of genes
simultaneously during important biological processes and across collections of related …

Sentiment analysis, commonly known as “opinion mining,” aims to identify sentiment
polarities in opinion texts. Recent years have seen a significant increase in the acceptance …