Intelligent data analysis for biomedical applications challenges and solutions
Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods a...
| Otros Autores: | , , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
London, United Kingdom :
Academic Press, an imprint of Elsevier
[2019]
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| Edición: | 1st edition |
| Colección: | Intelligent data centric systems.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631238706719 |
Tabla de Contenidos:
- IoT-Based intelligent capsule endoscopy system: a technical review
- Optimization of methods for image-texture segmentation using ant colony optimization
- A feature fusion-based discriminant learning model for diagnosis of neuromuscular disorders using single-channel needle electromyogram signals
- Evolution of consciousness systems with bacterial behaviour
- Analysis of transform-based compression techniques for MRI and CT images
- A medical image retrieval system in PACS environment for clinical decision making
- A neuro-fuzzy inference model for diabetic retinopathy classification
- Computational automated system for red blood cell detection and segmentation
- Evolutionary algorithm with memetic search capability for optic disc localization in retinal fudus images
- Classification of Myocardial Ischemia in delayed contrast enhancement using machine learning
- Simple-link sensor network-based remote monitoring of multiple patients
- Hybrid approach for classification of electroencephalographic signals using time-frequency images with wavelets and texture features.
