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Herausgeber: 
  • Babita Majhi
  • Subhendu Kumar Pani
  • Dash Sujata
  • Rodrigues Joel J. P. C.
  • Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics: Techniques and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Februar 2022  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Adaptive Median Filter / advanced biomedical signal analysis / Alzheimer’s Disease Neuroimaging Initiative / Chinese Longitudinal Healthy Longevity Survey / Classification Technique Support Vector Machine / Clinical decision support / CNN Model / computational biomedicine
    ISBN:  9780367544256 
    EAN-Code: 
    9780367544256 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Gewicht:  675 gr 
    Seiten:  362 
    Illustration:  schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. ¿ Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications ¿ Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches ¿ Discusses various techniques of IoT systems for healthcare data analytics ¿ Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics ¿ Focuses more on the application of algorithms in various real life biomedical and engineering problems

      



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