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Herausgeber: 
  • Miltiadis Lytras
  • Abdulrahman Housawi
  • Basim Alsaywid
  • Naif Radi Aljohani
  • Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2024  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / Artificial Intelligence (AI) / Biology, life sciences / Computational biology / bioinformatics / Computer modelling & simulation / COMPUTERS / Artificial Intelligence / General / Digital Health / Health Literacy
    ISBN:  9780443136191 
    EAN-Code: 
    9780443136191 
    Verlag:  Elsevier 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 191 mm / D  
    Gewicht:  710 gr 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Next Generation eHealth: Applied Data Science, Machine Learning and Extreme Computational Intelligence discusses the emergence, the impact, and the potential of sophisticated computational capabilities in healthcare. This book provides useful therapeutic targets to improve diagnosis, therapies, and prognosis of diseases, as well as helping with the establishment of better and more efficient next-generation medicine and medical systems. Machine learning as a field greatly contributes to next-generation medical research with the goal of improving medicine practices and medical Systems. As a contributing factor to better health outcomes, this book highlights the need for advanced training of professionals from various health areas, clinicians, educators, and social professionals who deal with patients. Content illustrates current issues and future promises as they pertain to all stakeholders, including informaticians, professionals in diagnostics, key industry experts in biotech, pharma, administrators, clinicians, patients, educators, students, health professionals, social scientists and legislators, health providers, advocacy groups, and more. With a focus on machine learning, deep learning, and neural networks, this volume communicates in an integrated, fresh, and novel way the impact of data science and computational intelligence to diverse audiences.

      



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