Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering

1. Auflage 2024
ISBN: 978-1-032-75923-4
Verlag: CRC Press

Buch, Englisch, 304 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 622 g

Reihe: Emerging Trends in Biomedical Technologies and Health informatics

This book provides a platform for presenting machine learning (ML)-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes ML techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.

Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering discusses the Internet of Things (IoT) and ML devices that are deployed for enabling patient health tracking, various emergency issues, and the smart administration of patients. It looks at the problems of cardiac analysis in e-healthcare, explores the employment of smart devices aimed at different patient issues, and examines the usage of Arduino kits where the data can be transferred to the cloud for Internet-based uses. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. The authors also examine the role of IoT and ML in electroencephalography and magnetic resonance imaging, which play significant roles in biomedical applications. This book also incorporates the use of IoT and ML applications for smart wheelchairs, telemedicine, GPS positioning of heart patients, and smart administration with drug tracking. Finally, the book also presents the application of these technologies in the development of advanced healthcare frameworks.

This book will be beneficial for new researchers and practitioners working in the biomedical and healthcare fields. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practices of medical image retrieval and brain image segmentation.

Zielgruppe

Postgraduate and Professional Reference

Autoren/Hrsg.

Kumar Rana, Arun

Sharma, Vishnu

Rana, Sanjeev Kumar

Chaudhary, Vijay Shanker

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1 Applications of Artificial Intelligence and Internet of Things in Healthcare Industries 2 Machine Learning for Internet of Medical Things Applications: Framework, Developments, and Challenges 3 IoT Healthcare's Advanced Decision Support through Computational Intelligence 4 Insights into Thyroid Disease: Harnessing Machine Learning for Analysis and Classification of Multi-Label Medical Data 5 Longitudinal Study on Non-Communicable Diseases Using Machine Learning 6 Uncovering Machine Learning Trends in Biomedical: Pulmonary Disease Diagnosis7 Smart Surgery: Navigating Precision through Machine Learning and IoT 8 Classification and Detection of Brain Tumors in MRI Images Using Machine Learning Techniques 9 Advanced Deep Learning for Early Alzheimer's Detection: A Comparative Analysis 10 Artificial Intelligence and Machine Learning in Biomedical Signal Processing 11 Machine Learning and Internet of Things Biomedical Technologies 12 Revolutionizing Chronic Kidney Disease Prediction: An Enhanced Semi-Supervised Learning Model 13 Analysing the Seamless Integration of Machine Learning and Internet of Things in the Daily Dynamics of Contemporary Living 14 Convergence of AR, VR, IoT with Artificial Intelligence to Train Surgeons for Medical Surgeries 15 An Overview of IoT and Machine Learning Approach in Healthcare 16 Healthcare Unbound: Navigating Emerging Trends and Future Applications in IoT-Based Innovations for Daily Well-being 17 Image-Guided Surgery Through ML and IOT

Über Autor(innen)

Arun Kumar Rana is currently Assistant Professor-3 in Galgotias College of Engineering and Technology, Greater Noida, India with more than 16 years of experience. His areas of interest includes image processing, wireless sensor network, Internet of Things, AI, and machine learning and embedded systems.

Vishnu Sharma is Professor and Dean CSE at ITS College of Engineering, Greater Noida India. Dr. Sharma completed his BTech, MTech, and PhD (CSE) in 2012 from the Government Autonomous Institute, Madhav Institute of Technology and Science (M.I.T.S.) Gwalior, MP, in Computer Science and Engineering, and was affiliated to Rajiv Gandhi Technical University, Bhopal, India. His areas of interest are mobile computing, cybersecurity, and advanced mobile computing.

Sanjeev Kumar Rana is Professor of Computer Science and Engineering at Maharishi Markandeshwar (deemed to be a university), Mullana-Ambala, India. He earned his PhD from Maharishi Markandeshwar University, Mullana-Ambala, India, in 2012. He is also a CISCO-certified instructor. His research interest includes distributed computing, network security, blockchain technology, and big data analytics.

Vijay Shanker Chaudhary is Assistant Professor (GCET, Greater Noida) and Researcher (photonic crystal fiber-based biosensors), He received his PhD from the Madan Mohan Malviya University of Technology, Gorakhpur, India. His research interests include photonic crystal fiber, optical fiber sensors, and terahertz sensing properties.