Handbook of computational intelligence in biomedical engineering and healthcare /
Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein stru...
Clasificación: | Libro Electrónico |
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Otros Autores: | , , , |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
London, United Kingdom :
Academic Press,
2021.
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Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Application of dynamical systems based deep learning algorithms to model emergent characteristics for healthcare diagnostics
- Computational intelligence in healthcare and biosignal processing
- A semi-supervised approach for automatic detection and segmentation of optic disc from retinal fundus image
- Medical decision support system using data mining : an intelligent health care monitoring system for guarded travel
- Deep learning in gastroenterology : a brief review
- Application of soft computing techniques to calculation of medicine dose during the treatment of patient : a fuzzy logic approach
- Multiobjective optimization technique for gene selection and sample categorization
- Medical decision support system using data mining semicircular-based angle-oriented facial recognition using neutrosophic logic
- Preservation module prediction by weighted differentially coexpressed gene network analysis (WDCGNA) of HIV-1 disease : a case study for cancer
- Computational intelligence for genomic data : a network biology approach
- A Kinect-based motor rehabilitation system for stroke recovery
- Empirical study on Uddanam chronic kidney diseases (UCKD) with statistical and machine learning analysis including probabilistic neutral networks
- Enhanced brain tumor detection using fractional wavelet transform and artificial neural network
- A study on smartphone sensor-based human activity recognition using deep learning approaches.