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Soft Computing for Biomedical Applications and Related Topics: Studies in Computational Intelligence, cartea 899

Editat de Vladik Kreinovich, Nguyen Hoang Phuong
en Limba Engleză Paperback – 30 iun 2021
This book presents innovative intelligent techniques, with an emphasis on their biomedical applications. Although many medical doctors are willing to share their knowledge – e.g. by incorporating it in computer-based advisory systems that can benefit other doctors – this knowledge is often expressed using imprecise (fuzzy) words from natural language such as “small,” which are difficult for computers to process. Accordingly, we need fuzzy techniques to handle such words. It is also desirable to extract general recommendations from the records of medical doctors’ decisions – by using machine learning techniques such as neural networks. The book describes state-of-the-art fuzzy, neural, and other techniques, especially those that are now being used, or potentially could be used, in biomedical applications. Accordingly, it will benefit all researchers and students interested in the latest developments, as well as practitioners who want to learn about new techniques. 


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Specificații

ISBN-13: 9783030495381
ISBN-10: 3030495388
Ilustrații: IX, 329 p. 195 illus., 123 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.48 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Multiagent Smart Communication Based on CI Technology.- Develop a Prediction Model for Nonmelanoma Skin Cancer Using Deep Learning in EHR data.- VectorDefense: Vectorization as a Defense to Adversarial Examples.- Artificial Intelligence in Infection Control—Healthcare Institutions Need Intelligent Information and Communication Technologies for Surveillance and Benchmarking.- Why some Non-Classical Logics are more Studied?.- Why h-index?.- Accuracy of Data Fusion: Interval (and Fuzzy) Case.- Imputing Missing Values: Reinforcement Bayesian Regression and Random Forest.- From Machine Learning to Knowledge-based Decision Support—A Predictive-Model-Markup-Language-to-Arden-Syntax Transformer for Decision Trees.

Textul de pe ultima copertă

This book presents innovative intelligent techniques, with an emphasis on their biomedical applications. Although many medical doctors are willing to share their knowledge – e.g. by incorporating it in computer-based advisory systems that can benefit other doctors – this knowledge is often expressed using imprecise (fuzzy) words from natural language such as “small,” which are difficult for computers to process. Accordingly, we need fuzzy techniques to handle such words. It is also desirable to extract general recommendations from the records of medical doctors’ decisions – by using machine learning techniques such as neural networks. The book describes state-of-the-art fuzzy, neural, and other techniques, especially those that are now being used, or potentially could be used, in biomedical applications. Accordingly, it will benefit all researchers and students interested in the latest developments, as well as practitioners who want to learn about new techniques. 



Caracteristici

Discusses recent research on soft computing for biomedical applications and related topics Presents applications and technical aspects of soft computing for biomedical problems Intended for practitioners and researchers alike, introducing them to the latest soft computing techniques