Machine Learning in Bio-Signal Analysis and Diagnostic Imaging (Paperback)

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. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	December 2018
First published:	2019
Editors:	Nilanjan Dey • Surekha Borra • Amira Ashour • Fuqian Shi
Dimensions:	235 x 191mm (L x W)
Format:	Paperback
Pages:	345
ISBN-13:	978-0-12-816086-2
Categories:	Books > Medicine > Other branches of medicine > Medical imaging > General Books > Medicine > Nursing & ancillary services > Biomedical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-12-816086-1
Barcode:	9780128160862

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