Full Description
Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare.
Contents
The impact of Internet of Things and data semantics on decision making for outpatient monitoring
Deep-learning approaches for health care: Patients in intensive care
Brain MRI image segmentation using nature-inspired Black Hole metaheuristic clustering approach
Blockchain for public health: Technology, applications, and a case study
Compression and multiplexing of medical images using optical image processing
Analysis of skin lesions using machine learning techniques
Computational intelligence using ontology—A case study on the knowledge representation in a clinical decision support system
Neural network-based abnormality detection for electrocardiogram time signals
Machine learning approaches for acetic acid test based uterine cervix image analysis
Convolutional neural network for biomedical applications
Alzheimer's disease classification using deep learning
Diabetic retinopathy identification using autoML
Knowledge-based systems in medical applications
Convolution neural network-based feature learning model for EEG-based driver alert/drowsy state detection
Analysis on the prediction of central line-associated bloodstream infections (CLABSI) using deep neural network classification
