Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Nonfiction, Science & Nature, Science, Biological Sciences, Biotechnology, Technology, Engineering, Health & Well Being, Medical
Cover of the book Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by , Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9780128160879
Publisher: Elsevier Science Publication: November 30, 2018
Imprint: Academic Press Language: English
Author:
ISBN: 9780128160879
Publisher: Elsevier Science
Publication: November 30, 2018
Imprint: Academic Press
Language: English

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.

  • Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging
  • Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining
  • Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Elsevier Science

Cover of the book Handbook of Categorization in Cognitive Science by
Cover of the book Eukaryotic RNases and their Partners in RNA Degradation and Biogenesis by
Cover of the book Pattern Recognition by
Cover of the book Principles of Environmental Physics by
Cover of the book Handbook of Fire and Explosion Protection Engineering Principles by
Cover of the book Laboratory Animals by
Cover of the book Treatise on Process Metallurgy, Volume 3: Industrial Processes by
Cover of the book Risk Management, Speculation, and Derivative Securities by
Cover of the book Nanotechnology in Water and Wastewater Treatment by
Cover of the book Valuation by
Cover of the book Compendium of Hydrogen Energy by
Cover of the book Agile Manufacturing: The 21st Century Competitive Strategy by
Cover of the book Non-Destructive Evaluation (NDE) of Polymer Matrix Composites by
Cover of the book Plant Cell Biology by
Cover of the book Analytical Methods for Agricultural Contaminants by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy