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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Nayak, Janmenjoy, Naik, Bighnaraj, Pelusi, Danilo, Das, Asit Kumar (Computer scientist)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London, United Kingdom : Academic Press, 2021.
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.