Predictive Intelligence in Biomedical and Health Informatics

Ashish Khanna

ISBN 10: 3110676087 / ISBN 13: 9783110676082

Published by De Gruyter, DE, 2020

About this Item

Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Seller Inventory # LU-9783110676082

Bibliographic Details

• Title: Predictive Intelligence in Biomedical and Health Informatics
• Publisher: De Gruyter, DE
• Publication Date: 2020
• Language: English
• ISBN 10: 3110676087
• ISBN 13: 9783110676082
• Binding: Hardback
• Condition: New
• Dimensions: 15.49W x 2.03H x 23.11D centimeters 15.49 centimeters width by 2.03 centimeters height by 23.11 centimeters depth
• Weight: 454 grams

About this title

Synopsis

Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

About the Author

R. Srivastava, DIT Univ., A. Khanna, Agrasen Institute, S.Bhattacharyya, RCC Institute, India; N. Nhu, Duy Tan Univ., Vietnam.