Machine Learning: An Effective Technique in Bio-Medical Signal Analysis and Classification

Abstract

Advancement in the field of digital signal processing and modern machine learning (ML) approaches has witnessed substantial growth in biomedical engineering. The diagnostic power of these machines has grown manifolds mainly due to the exploration of effective and discriminate feature spaces that remain crucial for pattern recognition. It has enhanced the ability of machine learners to model the complex patterns accurately and make them adaptable to new task domains with explanation/experience learning approaches. Many vivid application domains including the artificial intelligent systems and robotics with critical and innovative thinking are going to rely on effective ML systems for efficiency and optimization. This has made the Artificial Neural Networks (NN) an emerging field of research and motivates the authors to classify the MIT-BIH arrhythmia data as abnormal or normal using different ANN models. Finally, the results have been validated with that of the colon cancer gene data.