Soft Computing for Biomedical Applications and Related Topics

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Geliefert zwischen Mo., 29.12.2025 und Di., 30.12.2025

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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.




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

Inhalt
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 ControlHealthcare 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 SupportA Predictive-Model-Markup-Language-to-Arden-Syntax Transformer for Decision Trees.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783030495381
    • Genre Technology Encyclopedias
    • Auflage 1st edition 2021
    • Editor Nguyen Hoang Phuong, Vladik Kreinovich
    • Lesemotiv Verstehen
    • Anzahl Seiten 340
    • Herausgeber Springer International Publishing
    • Größe H235mm x B155mm x T19mm
    • Jahr 2021
    • EAN 9783030495381
    • Format Kartonierter Einband
    • ISBN 3030495388
    • Veröffentlichung 30.06.2021
    • Titel Soft Computing for Biomedical Applications and Related Topics
    • Untertitel Studies in Computational Intelligence 899
    • Gewicht 517g
    • Sprache Englisch

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