Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Nilanjan Dey, Surekha Borra, Amira S. Ashour, Fuqian Shi
Elsevier S&T
345 pages
ISBN-13: 978-0128160862
December 2018

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented.