Machine learning for critical Internet of medical things : applications and use cases / Fadi Al-Turjman, Anand Nayyar, editors.
Al-Turjman, Fadi, editor.; Nayyar, Anand, editor.
2022
R859.7.A78 M33 2022
Available Online

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Title Machine learning for critical Internet of medical things : applications and use cases / Fadi Al-Turjman, Anand Nayyar, editors.
ISBN 9783030809287 (electronic bk.)
3030809285 (electronic bk.)
9783030809270
3030809277
DOI https://doi.org/10.1007/978-3-030-80928-7
Published Cham : Springer, [2022]
Copyright ©2022
Language English
Description 1 online resource : illustrations (chiefly color)
Other Standard Identifiers 10.1007/978-3-030-80928-7 doi
Call Number R859.7.A78 M33 2022
Dewey Decimal Classification 610.285/63
Summary 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 physicians and doctors 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.
Note Includes index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 17, 2022).
Added Author Al-Turjman, Fadi, editor.
Nayyar, Anand, editor.
Available in Other Form Print version: 9783030809270
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Introduction
An Introduction to Basic Concepts on Machine Learning, its architecture and framework
Machine Learning Models and techniques
Diseases diagnosis and prediction using Machine Learning
Machine learning for Mobile/e-health, Tele-medical and Remote healthcare networks
Machine learning in biomedical, Neuro-critical and medical image processing field
AI, Deep learning and machine learning enabled connected health informatics
Machine learning enabled smart healthcare system
Machine learning based efficient health monitoring systems
Machine learning case study for virus disease Ebola, COVID-19 consequences
CASE Study: Machine Learning in Medical domain for Cervical Cancer
Use cases and applications of machine learning in medical domain
Conclusion.

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