Machine Learning for Critical Internet of Medical Things (e-bog) af -
Nayyar, Anand (redaktør)

Machine Learning for Critical Internet of Medical Things e-bog

1313,81 DKK (inkl. moms 1642,26 DKK)
This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast ...
E-bog 1313,81 DKK
Forfattere Nayyar, Anand (redaktør)
Forlag Springer
Udgivet 3 februar 2022
Genrer Cybernetics and systems theory
Sprog English
Format epub
Beskyttelse LCP
ISBN 9783030809287
This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physician's and doctor's medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system.Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas;Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer;Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.