Classification in BioApps
Automation of Decision Making
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Beschreibung
This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges.
Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization.
This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges.
Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization.
In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.
Provides broad background information on and solutions to existing challenges in classifiers used for biomedical applications Addresses various applications for the classification of biomedical signals from consumer and industry perspectives Highlights recent developments and topics of interest in machine learning techniques for the classification of biomedical signals Discusses the design and performance analysis of various existing classification techniques Includes standards for, challenges in, and recommendations for classifiers in biomedical applications Includes supplementary material: sn.pub/extras
Autor*in
Nilanjan Dey
Themen in »Classification in BioApps«
Bio-medical signal/image analysis Decision support systems Machine learning Support vector machine Feature extraction and Feature selection Optimization algorithms