Machine Learning in Bio-Signal Analysis and Diagnostic Imaging Contributor(s): Dey, Nilanjan (Editor), Borra, Surekha (Editor), Ashour, Amira S. (Editor) |
|||
ISBN: 0128160861 ISBN-13: 9780128160862 Publisher: Academic Press
Binding Type: Paperback Published: December 2018 |
Additional Information |
BISAC Categories: - Science | Biotechnology - Technology & Engineering | Biomedical |
LCCN: 2021303161 |
Physical Information: 0.72" H x 7.5" W x 9.25" L (1.31 lbs) 345 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |
Customer ReviewsSubmit your own review |
To tell a friend about this book, you must Sign In First! |