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Soft computing for biomedical applic...

Kreinovich, Vladik.

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Soft computing for biomedical applications and related topics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Soft computing for biomedical applications and related topics/ edited by Vladik Kreinovich, Nguyen Hoang Phuong.
其他作者:	Kreinovich, Vladik.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	ix, 329 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Soft computing. -
電子資源:	https://doi.org/10.1007/978-3-030-49536-7
ISBN:	9783030495367

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. 899..

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

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

563033
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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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.
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