Computational Intelligence and Its Applications in Healthcare 1st edition by Jitendra Kumar Verma, Sudip Paul, Prashant Johri – Ebook PDF Instant Download/Delivery: 0128206195, 9780128206195
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Product details:
ISBN 10: 0128206195
ISBN 13: 9780128206195
Author: Jitendra Kumar Verma, Sudip Paul, Prashant Johri
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.
Computational Intelligence and Its Applications in Healthcare 1st Table of 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
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Tags: Jitendra Kumar Verma, Sudip Paul, Prashant Johri, Computational Intelligence, Its Applications


