Deep Learning in Internet of Things for Next Generation Healthcare
Chapman & Hall/CRC (Verlag)
978-1-032-58610-6 (ISBN)
This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes.
Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics
Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more
Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare
Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications
Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges
Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.
Dr. Lavanya Sharma is an assistant professor, Amity Institute of Information Technology at Amity University UP, Noida, India. She did her M.Tech (Computer Science and Engineering) in 2013 at Manav Rachna College of Engineering, affiliated with Maharshi Dayanand University, Haryana, India. She did her Ph.D. at Uttarakhand Technical University, India, as a full time Ph.D. Scholar in the field of Digital Image Processing and Computer Vision in April 2018 and received a TEQIP scholarship for the same. Her research work is on motion-based object detection using a background subtraction technique for smart video surveillance. She has been a recipient of several prestigious awards during her academic career. She has more than 40+ research papers to her credit, including Elsevier (SCI indexed), Inderscience, IGI Global, IEEE Explore, and many more. She has authored six books and five with Taylor & Francis, CRC Press. She has done various certified courses from IIRS (ISRO Dehradun Unit) and also guided 90+. She also contributed as an organizing committee member to Springer’s Springer and IEEE conferences. She is an editorial member/reviewer of various journals of repute and active program committee member of various IEEE and Springer conferences. Her primary research interests are digital image processing and computer vision, artificial intelligence, mobile ad-hoc networks, and the Internet of Things. Her vision is to promote teaching and research, providing a highly competitive and productive environment in academic and research areas with tremendous growing opportunities for society and her country. Professor P.K. Garg worked as a Vice Chancellor, Uttarakhand Technical University, Dehradun. Presently he is working in the department of Civil Engineering, IIT Roorkee, as a professor. He completed a B.Tech. (civil engineering) in 1980 and M.Tech. (civil engineering) in 1982, both from the University of Roorkee (now IIT Roorkee). He is a recipient of the Gold Medal at IIT Roorkee to stand first during the M.Tech program, Commonwealth Scholarship Award for doing his Ph.D. at the University of Bristol (UK), and Commonwealth Fellowship Award to carry out post-doctoral research work at the University of Reading (UK). He joined the Department of Civil Engineering at IIT Roorkee in 1982, and gradually advancing, his career rose to the position of Head of the department in 2015 at IIT Roorkee. Professor Garg has published more than 300 technical papers in national and international conferences and journals. He has undertaken 26 research projects and provided technical services to 83 consultancy projects on various aspects of Civil Engineering, generating funds for the Institute. He has authored three text-books on remote sensing, theory and principles of geoinformatics, and introduction to unmanned aerial vehicles and produced two technical films on the story of mapping. He has developed several new courses and practical exercises in Geomatics Engineering. Besides supervising a large number of undergraduate projects, he has guided about 72 M.Tech. and 27 Ph.D. thesis students. He is instrumental in prestigious MHRD-funded projects on e-learning and the development of virtual labs, pedagogy and courses under NPTEL. He has served as an expert on various national committees, including the Ministry of Environment & Forest; EAEC Committee; NBA (AICTE); and Project Evaluation Committee, DST, New Delhi. Professor Garg has reviewed a large number of papers for national and international journals. Considering the need to train human resources in the country, he has successfully organized 42 programs in advanced areas of surveying, photogrammetry, remote sensing, GIS, and GPS. He has successfully organized ten conferences and workshops. He is a life member of 24 professional societies, out of which he is a fellow of eight societies. For academic work, Professpr Garg has traveled widely, nationally and internationally.
1. Rise of communications devices to IoT 2. Architecture framework for IoT and deep learning system 3. Deep learning and human vision in IoT 4. Impact of IoT on big data analytics and applications in Medical Images 5. Geospatial data collection tools in healthcare 6. Geospatial technologies in healthcare 7. Advancement of Geospatial Technology in Healthcare systems 8. Implementation of Deep Learning in Assessment of Health Hazardous Air Pollutants 9. Technological interventions in Healthcare 10. Disaster and emergency healthcare 11. Cloud Frameworks for Deep Learning and IoT based Applications in Healthcare Domain 12. Improvement of Patient Care using Robotics in the Healthcare Industry 13. Deep learning Processes in MRI images 14. Artificial Intelligence and Robotics in Healthcare: Transforming the Indian Landscape 15. Medical Insurance Fraud Detection 16. Privacy and Security Issues for IoT and Deep Learning in Next Generation Healthcare: An Indian Perspective 17. A Systematic Review on the Future of Internet of Things Applications in Healthcare 18. 6G Network Development and 3D Holography in Future Healthcare 19. Tracking of disease- A review of state of the art of technology for next generation healthcare 20. Disease detection using Tensor Flow Methodology 21. AI and Deep Learning: Applications in Healthcare
| Erscheinungsdatum | 13.06.2024 |
|---|---|
| Zusatzinfo | 5 Tables, black and white; 70 Line drawings, black and white; 12 Halftones, black and white; 82 Illustrations, black and white |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 730 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Informatik ► Web / Internet | |
| Informatik ► Weitere Themen ► Hardware | |
| Medizin / Pharmazie ► Gesundheitswesen | |
| Recht / Steuern ► Privatrecht / Bürgerliches Recht ► IT-Recht | |
| ISBN-10 | 1-032-58610-9 / 1032586109 |
| ISBN-13 | 978-1-032-58610-6 / 9781032586106 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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