This book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.
This book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers around the world.
Dr. Arun Kumar Rana is currently an Assistant Professor-3 in Galgotias College of Engineering and Technology, Greater Noida, India with more than 16 years of experience. His area of interest includes Image Processing, Wireless Sensor Network, Internet of Things, AI, and Machine Learning and Embedded systems. Dr Vishnu Sharma is a Professor and Dean CSE at ITS College of Engineering, Greater Noida India. Dr. Vishnu Sharma completed his B.Tech, M.Tech, and Ph.D. (CSE) in 2012 from Gov. Autonomous Institute, Madhav Institute of Technology & Science (M.I.T.S.) Gwalior (M.P.) in Computer Science & Engineering and Affiliated to Rajiv Gandhi Technical University, Bhopal, India. His areas of interest are mobile computing, cybersecurity, and advanced mobile computing. Dr. Sanjeev Kumar Rana is a Professor of Computer Science and Engineering at Maharishi Markandeshwar (deemed to be university), Mullana-Ambala, India. He earned his PhD degree 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, big data analytics. Vijay Shanker Chaudhary is an Associate Professor (GCET, Greater Noida) and Researcher (Photonic Crystal Fiber Based Biosensors), He received his PhD degree from the Madan Mohan Malviya University of Technology, Gorakhpur, India. His research interests include photonic crystal fiber, optical fiber sensors, and terahertz sensing properties.
Inhaltsangabe
1. Applications of Artificial Intelligence and Internet of Things in Healthcare Industries. 2. ML 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 Diagnosis. 7. 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 & Machine Learning Approach in Health Care. 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.
1. Applications of Artificial Intelligence and Internet of Things in Healthcare Industries. 2. ML 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 Diagnosis. 7. 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 & Machine Learning Approach in Health Care. 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.
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