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Soft computing for biomedical applic...

Hoang Phuong, Nguyen.

Soft computing for biomedical applications and related topics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Soft computing for biomedical applications and related topicsedited by Vladik Kreinovich, Nguyen Hoang Phuong.
other author:	Kreinovich, Vladik.
Published:	Cham :Springer International Publishing :2021.
Description:	ix, 329 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Soft computing.
Online resource:	https://doi.org/10.1007/978-3-030-49536-7
ISBN:	9783030495367$q(electronic bk.)

Soft computing for biomedical applications and related topics
Soft computing for biomedical applications and related topics[electronic resource] /edited by Vladik Kreinovich, Nguyen Hoang Phuong. - Cham :Springer International Publishing :2021. - ix, 329 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 8991860-9503 ;. - Studies in computational intelligence ;v. 216..

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.

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.

ISBN: 9783030495367$q(electronic bk.)

Standard No.: 10.1007/978-3-030-49536-7doiSubjects--Topical Terms:

182083
Soft computing.

LC Class. No.: QA76.9.S63 / S64 2021

Dewey Class. No.: 006.3

Soft computing for biomedical applications and related topics
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245 0 0 $a Soft computing for biomedical applications and related topics $h [electronic resource] / $c edited by Vladik Kreinovich, Nguyen Hoang Phuong.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a ix, 329 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 899
505 0 $a 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.
520 $a 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.
650 0 $a Soft computing. $3 182083
650 0 $a Biomedical engineering. $3 190330
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Engineering Mathematics. $3 806481
650 2 4 $a Biomedical Engineering and Bioengineering. $3 826326
700 1 $a Kreinovich, Vladik. $3 610822
700 1 $a Hoang Phuong, Nguyen. $3 915008
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950 $a Intelligent Technologies and Robotics (SpringerNature-42732)