Healthcare Industry 4.0

Computer Vision-Aided Data Analytics
1. Auflage 2023
ISBN: 978-1-032-38515-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 186 Seiten, Format (B × H): 156 mm x 239 mm, Gewicht: 422 g

Reihe: Computational Intelligence Techniques

This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring.

Features:

- Provides a state-of-the-art computer vision application in the digital health care industry

- Reviews advances in computer vision and data science technologies for analyzing information on human function and disability

- Includes practical implementation of computer vision application using recent tools and software

- Explores computer vision-enabled medical/clinical data security in the cloud

- Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google

This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Karthikeyan, P.

Katina, Polinpapilinho F.

Rajagopal, R.

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

1. Introduction to Computer Vision Aided Data Analytics in Healthcare Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time Health Care System 5. Modality Classification of Human Emotion 6. COVID-19 Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of Computer Vision Application in Digital Healthcare 10. Study of Computer Vision Applications in Healthcare Industry 4.0

Über Autor(innen)

P. Karthikeyan obtained his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, and Tamil Nadu, India, in 2005 and received his Master of Engineering (M.E.) in Computer Science and Engineering from Anna University, Coimbatore, India, in 2009. He completed his Ph.D. degree in ICE from the Anna University, Chennai, in 2018. He is currently completing postdoctoral research at National Chung Cheng University, Taiwan. He is skilled in developing projects and carrying out research in the area of cloud computing and deep learning with programming skills in Java, Python, R and C. He published over 20 articles in international journals with high impact factors and has presented his work at more than 10 international conferences. He has served as a reviewer for prestigious publishers such as Elsevier, Springer, and Inderscience, as well as Scopus indexed journals. Additionally, he currently serves as an editorial board member for several journals, including the EAI Endorsed Transactions on Energy Web, The International Arab Journal of Information Technology and Blue Eyes Intelligence Engineering and Sciences Publication Journal.

Polinpapilinho F. Katina is an Assistant Professor in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate, Spartanburg, South Carolina, USA. He previously served as a Postdoctoral Researcher for the National Centers for System of Systems Engineering in Norfolk, Virginia, USA, and Adjunct Professor in the Department of Engineering Management and Systems Engineering at Old Dominion University, Norfolk, Virginia, USA. Dr. Katina holds a B.Sc. in Engineering Technology with a minor in Engineering Management, a M. Eng. in Systems Engineering, and a Ph.D. in Engineering Management/Systems Engineering, all from Old Dominion University. He has received additional training from, among others, the Environmental Systems Research Institute in Redlands, California, USA, and Politecnico di Milano in Milan, Italy. His areas of research/teaching include, among others, complex system governance, critical infrastructure systems, decision-making and analysis (under uncertainty), emerging technologies, energy systems (smart grids), engineering management, infranomics, manufacturing systems, system of systems, systems engineering, systems pathology, and systems thinking.

R. Rajagopal received his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, and Tamil Nadu, India, in 2005, his Master of Engineering (M.E.) in Computer Science and Engineering from Anna University, Coimbatore, India, in 2009, and his Ph.D. degree in Anna University, Chennai, in 2018. He has served as a reviewer for reputed Scopus indexed journals and Inderscience. He is also an editorial board member of several journals, including the International Journal of Mathematical Science, Engineering, and Sciences Publication. His research work has been published in over 22 international journals, and he has presented at more than 20 international conferences.