Synopsis
The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Dr. Neha Goel is working as Professor in the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. She has Ph.D. degree from SRM University, Chennai, in 2019. She has 18 years of rich experience in teaching and research and development activities. Her area of interest is VLSI design, CMOS design, Internet of Things, and machine learning. She has guided several B.Tech and M.Tech Projects and has published 45 papers in various national/ international journals and conferences. She has received many grants and has published Four patents. She has also attended various workshops and seminars in various fields.
Dr. Ravindra Kumar Yadav is Professor and Head of the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. He has B.E., M.E., and Ph.D. degrees in the field of Electronics & Communication Engineering. He has 26 years of rich experience in teaching, research and development activities, administration and managing, and establishing higher educational institutions. He has guided several B. Tech. and M.Tech. projects and is also guiding Ph.D. students from IIT Dhanbad as a co-guide. He has 90 papers to his credit, published in international/national journals, conferences, and symposiums. Prof. Yadav is reviewer for several national/international journals of high repute. He has chaired/participated in technical sessions at multiple international and national conferences/seminars held throughout the country.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Internet of Things enabled Machine Learning for Biomedical Applications (Hardcover)
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Taylor & Francis Ltd, London, 2024
ISBN 10 : 1032550821
ISBN 13 : 9781032550824
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Hardcover. Etat : new. Hardcover. The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.This book:Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learningHighlights security and privacy issues in the healthcare system using the Internet of ThingsDiscusses classification and implementation techniques of image segmentationExplains different algorithms of machine learning for image processing in a comprehensive mannerProvides computational intelligence on the Internet of Things for future biomedical applications including lung cancerIt is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering. The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781032550824
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Neha Goel is working as Professor in the Department of Electronics & Communication Engineering, RKGIT, Ghaziabad, India. She has Ph.D. degree from SRM University, Chennai, in 2019. She has 18 years of rich experience in teaching and research and . N° de réf. du vendeur 1391355655
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Image d'archives
Internet of Things enabled Machine Learning for Biomedical Applications (Hardcover)
Edité par
Taylor & Francis Ltd, London, 2024
ISBN 10 : 1032550821
ISBN 13 : 9781032550824
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images.This book:Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learningHighlights security and privacy issues in the healthcare system using the Internet of ThingsDiscusses classification and implementation techniques of image segmentationExplains different algorithms of machine learning for image processing in a comprehensive mannerProvides computational intelligence on the Internet of Things for future biomedical applications including lung cancerIt is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering. The text begins by highlighting the benefits of the internet of things enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and examines security and privacy issues in the healthcare systems using the internet of things. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032550824
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