Detection of sickle cell disease is a crucial job in medical image analysis. It emphasizes
elaborate analysis of proper disease diagnosis after accurate detection followed by a …

Computer aided fusion of multi-modality medical images provides a very promising
diagnostic tool with numerous clinical applications. The objective of this paper is to present …

Abstract The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …

EMG signal decomposition is the process of resolving a composite EMG signal into its
constituent motor unit potential trains (classes) and it can be configured as a classification …

This study presents a new approach to determine the significant prognosis factors in dengue
patients utilizing the self-organizing map (SOM). SOM was used to visualize and determine …

This paper evaluates the classification of multisample problems, such as electromyographic
(EMG) data, by making aggregate features available to a per-sample classifier. It is found …

Recent technological advances in medicine has facilitated the development of sophisticated
equipment enabling the better delivery of health care services. In parallel, artificial neural …

The self-organizing feature map (SOFM or SOM) neural network approach has been applied
to a number of life sciences problems. In this paper, we apply SOFMs in predicting the …

This study investigates a new approach to determine the correlations between alpha (α)
electroencephalography (EEG) and other physiological parameters during Muslim prayer …

Aircraft engine fault diagnosis plays a crucial role in cost-effective operations of aircraft
engines. However, designing an engine fault diagnostic system with the desired …