Computational Intelligence and Its Applications in Healthcare

Computational intelligence is the study of the design of intelligent agents. An intelligent agent is a system that acts intelligently - it does what it thinks appropriate for its circumstances and its goal, it is flexible to changing environments and changing goals, it learns from experience, and it makes appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. Computational Intelligence and Its Applications in Healthcare presents rapidly growing application areas of computational intelligence to healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, analysis of user acceptance, pictures archiving and communication systems. Provides coverage of fuzzy logic, neural networks, Evolutionary computation, learning theory, probabilistic methods, telemedicine and robotics applicationsIncludes coverage of Artificial Intelligence and biological applications, soft computing, image processing and signal processing, and genetic algorithmsPresents the latest developments in computational methods in healthcareBridges the gap between obsolete literature and current literature INDICE: 1. The impact of Internet-of-Things and Data Semantics on the Decision Making for Outpatients' Monitoring 2. Deep learning approaches for Healthcare: Patients in Intensive care 3. Brain MRI Image Segmentation Using Nature Inspired Black Hole Metaheuristic Clustering Approach 4. Blockchain for Public Health: Technology, Applications, and a Case Study 5. Compression and Multiplexing of Medical Images using Optical Image Processing 6. Analysis of Skin Lesions using machine learning techniques 7. Computational Intelligence using Ontology - A Case Study on the Knowledge Representation in a Clinical Decision Support System 8. Neural Network Based Abnormality Detection for Electrocardiogram Time Signals 9. Machine Learning Approaches for Acetic Acid Test Based Uterine Cervix Image Analysis 10. Convolutional Neural Network for Biomedical Applications 11. Alzheimer's Disease Classification Using Deep Learning 12. Deep convolutional neural networks with architecture search technique for identification of diabetic retinopathy 13. Knowledge Based Systems in Medical Applications 14. Convolution Neural Network-based Feature Learning Model for EEG based Driver Alert/Drowsy State Detection 15. Multi Hop programming in medical development using semantic analysis and natural language processing techniques 16. Analysis on The Prediction of Central Line-Associated Bloodstream Infections (Clabsi) Using Deep Neural Network Classification

• ISBN: 978-0-12-820604-1
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 332
• Fecha Publicación: 01/07/2020
• Nº Volúmenes: 1
• Idioma: Inglés