Hypoacusis is the most prevalent sensory disability in the world and consequently, it can
lead to impede speech in human beings. One best approach to tackle this issue is to …

Support vector machine (SVM) is a popular pattern classification method with many diverse
applications. Kernel parameter setting in the SVM training procedure, along with the feature …

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 …

Objective Recent advances in artificial intelligence (AI) are driving innovative new health
care solutions. We aim to review the state of the art of AI in otology and provide a discussion …

The primary objective of this paper is to develop a methodology for brain tumor
segmentation. Nowadays, brain tumor recognition and fragmentation is one among the …

In this paper, we develop a diagnosis model based on particle swarm optimization (PSO),
support vector machines (SVMs) and association rules (ARs) to diagnose erythemato …

This paper hybridizes the gravitational search algorithm (GSA) with support vector machine
(SVM) and makes a novel GSA-SVM hybrid system to improve classification accuracy with …

Brain tumor is one of the major causes of death among other types of the cancer because
brain is a very sensitive, complex and central part of the body. Proper and timely diagnosis …

Disease forecasting using soft computing techniques is major area of research in data
mining in recent years. To classify heart and diabetes diseases, this paper proposes a …

Removing the redundant features from massive data collected from power systems is of
paramount importance in improving the efficiency of data-driven diagnostic systems. This …