Biomedical Applications of AI and IoMT in Smart Healthcare

Inbunden, Engelska, 2027

Del i serien Innovations in Intelligent Internet of Everything IoE

2 299 kr

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Beskrivning

Artificial Intelligence (AI) to the Internet of Medical Things (IoMT) is not just a slight enhancement of healthcare but a paradigm shift. Biomedical Applications of AI and IoMT in Smart Healthcare is a pioneering investigation of this change, filling the divide between highly complex computational methods and the practical clinical applications. This volume includes the most promising products to transform modern medicine, based on real-time monitoring of patients and mental health, to early detection of diabetes, hepatitis C, and skin cancers. This book, edited by a renowned group of professionals, Prashant Upadhyay, Pradeep Tomar, Fadi Al-Turjman and Satya Prakash Yadav, is an assemblage of research work around the world that explores practical applications as well as analytical frameworks. The topics addressed in chapters are quite broad, such as AI-based virtual tutors to learn medicine, HOG-based eye-tracking interfaces, hybrid deep learning networks to diagnose melanoma, and optimized neural networks to diagnose diseases. The book is not only focused on the level of sophistication in technology but also on the accessibility, equity, and the health impact on the world. This volume provides a valuable and timely guide to the ecosystem of the IoMT whether you are a researcher, biomedical engineer, health professional or student of digital health technologies. It shows how smart systems are turning healthcare into a more predictive, personalized and pervasive one algorithm at a time. Key Features: Varied Disease Coverage- Covers specialized AI/IoMT models of diabetes, cervical cancer, hepatitis C, monkeypox, melanoma, asthma, blood group classification, demonstrating a wide clinical applicability.Real-World IoMT Integration – A chapters deal with real-time data analysis, patient monitoring, wearable devices, and edge-based fitness coaching with geospatial technology and small language models.State-of-the-art AI and ML Approaches – Shows ensemble, transfer learning (ResNet-50 + SVM), perceptron optimization (Penguin Optimization Algorithm), and HOG-based face landmark detection.International & Multidisciplinary Authorship - The works of various universities and research centers in India, Turkey, and others will be involved, which will guarantee a multinational outlook to the topic of smart healthcare innovation.Bridging Research and Education - Unique focus on AI-powered medical education, virtual tutors, and simulation technologies, which makes it useful in both an academic and clinical training setting.

Produktinformation

Utgivningsdatum:2027-01-21
Mått:178 x 254 x undefined mm
Format:Inbunden
Språk:Engelska
Serie:Innovations in Intelligent Internet of Everything IoE
Antal sidor:408
Förlag:Taylor & Francis Ltd
ISBN:9781032955926

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Mer om författaren

Dr. Prashant Upadhyay (SMIEEE, MACM, MIFERP) is an Assistant Professor at Bennett University. He is concurrently a Post-Doctoral Research Fellow at the National Kaohsiung University of Science and Technology in Taiwan. His scholarly output includes the publication of 7 journal articles, 13 conference papers, and 20 book chapters. He has also authored one book, edited 7 books, and been awarded 9 Indian utility patents and 3 design patents. An active member of the academic community, Dr. Upadhyay has served as a session chair at several international conferences, including GTSS-2026, ICDT-2024, ICDETGT-2023, and ICDT-2023.Dr. Pradeep Tomar has been working as faculty in the University School of Information and Communication Technology, Gautam Buddha University, Greater Noida, U.P., India since 2009. Dr. Tomar earned his Ph.D. from MDU, Rohtak, Haryana, India. Dr. Tomar has excellent teaching, research, and software development experience as well as vast administrative experience at the university level on various posts. His major current research interest is in Software Engineering, Artificial Intelligence and Soft Computing Techniques. He has supervised more than 90+ M.Tech. Dissertations and 10+ Ph.D. under his guidance and he is guiding various research scholars in the above research area. He is a Investigator and Co-investigator in various sponsored research project. He has also filed more than 8 patents and 03 granted at the national and international levels. He has also contributed more than 200+ papers/articles/chapters in national/international journals & conferences and more than 10 books with national and international publishers.Prof. Dr. Fadi Al-Turjman received his Ph.D. in computer science from Queen’s University, Canada, in 2011. He is the associate dean for research and the founding director of the International Research Center for AI and IoT at Near East University, Nicosia, Cyprus. Prof. Al-Turjman is the head of Artificial Intelligence Engineering Dept., and a leading authority in the areas of smart/intelligent IoT systems, wireless, and mobile networks’ architectures, protocols, deployments, and performance evaluation in Artificial Intelligence of Things (AIoT). His publication history spans over 400 SCIE publications, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 40 books about cognition, security, and wireless sensor networks’ deployments in smart IoT environments, which have been published by well-reputed publishers such as Taylor and Francis, Elsevier, IET, and Springer. He has received several recognitions and best papers’ awards at top international conferences. He also received the prestigious Best Research Paper Award from Elsevier Computer Communications Journal for the period 2015-2018, in addition to the Top Researcher Award for 2018 at Antalya Bilim University, Turkey. Prof. Al-Turjman has led a number of international symposia and workshops in flagship communication society conferences.Currently, he serves as book series editor and the lead guest/associate editor for several top tier journals, including the IEEE Communications Surveys and Tutorials (IF 23.9) and the Elsevier Sustainable Cities and Society (IF 7.8), in addition to organizing international conferences and symposiums on the most up to date research topics in AI and IoT.Dr. Satya Prakash Yadav (FIETE & SMIEEE) is currently the Associate Professor of the Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, U.P. , India. He is also as Associate Dean R &D and Professional Practices. Dr. Yadav has done his Postdoctoral Research Fellow from Federal Institute of Education, Science and Technology of Ceará, Brazil. He has awarded his PhD degree from Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). Currently, 4 students are working for Ph.D. under his guidance. A seasoned academician having more than 18 years of experience, he has published four books (Programming in C, Programming in C++ and Blockchain and Cryptocurrency) under I.K. International Publishing House Pvt. Ltd. Including Distributed Artificial Intelligence: A Modern Approach, Published December 18, 2020 by CRC Press. He has undergone industrial training programs during which he was involved in live projects with companies in the areas of SAP, Railway Traffic Management Systems, and Visual Vehicles Counter and Classification (used in the Metro rail network design). He is an alumnus of Netaji Subhas Institute of Technology (NSIT), Delhi University. A prolific writer, Dr. Satya Prakash Yadav has published six patents and authored many research papers in web of science indexed journals. Additionally, His area of specialisation is in the areas of Image Processing, Information retrieval and Features extraction. Also, he is a Editor in Chief in Journal of Cyber Security in Computer System & Journal of Soft Computing and Computational Intelligence (MAT journals), Series Editor in DeGruyter International Publisher, Bentham Science and CRC Press, Taylor and Francis Group Publisher (U.S.A).

Innehållsförteckning

Chapter 1: Empowering the Future: The Role of AI and IOMT. Chapter 2: Big Data and Machine Learning Integration for Real-time Insights from IoMT Devices. Chapter 3: The Role of AI and IoMT in Global Health Initiatives. Chapter 4: Developing a Smart Healthcare Solution for Diabetes disease early prediction using Machine Learning classification algorithm, k-fold cross-validation and Ensemble Techniques. Chapter 5: Revolutionizing Healthcare: The Impact of AI and IoMT on Biomedical Advancement. Chapter 6: IoMT-Enabled Patient Monitoring and Management. Chapter 7: AI Integrated Mental Health Care Apps: Current and Emerging Trends. Chapter 8: Leveraging Machine Learning Algorithms for Real-time Data Analysis in IoMT Devices. Chapter 9: Blood Group Testing Using Various Machine Learning Techniques. Chapter 10: Transforming Cervical Cancer Detection: The Role of Artificial Intelligence in Early Diagnosis and Care. Chapter 11: Real-Time Eye-Tracking Mouse Control Using HOG-Based Facial Landmark Detection. Chapter 12: A.I. & BIG DATA IN HEALTHCARE DIAGNOSIS PREDICTION: REVIEW. Chapter 13: AI-Driven Virtual Tutors: Bridging the Gap between Traditional and Online Education. Chapter 14: Employment of Machine Learning Techniques for Identifying various skin diseases: A Study. Chapter 15: AI-Based Smart Healthcare System. Chapter 16: Automated Detection of Monkeypox Skin Infections: An Image Classification Approach. Chapter 17: An Advanced Hybrid Model Based on Transfer Learning: Utilizing ResNet-50 and Support Vector Machine for Melanoma Detection in Dermoscopic Images. Chapter 18: Hepatitis C Detection Using an Optimized Perceptron Neural Network with the Penguin Optimization Algorithm. Chapter 19: Diabetes Detection Using Machine Learning Algorithms on the PIMA Dataset. Chapter 20: Revolutionizing Medical Education: The Role of AI, Virtual Reality, and Simulation Technologies. Chapter 21: Role of Deep Learning Algorithms for Early Prediction of Health Diseases: A Case Study of Asthma Disease Prediction. Chapter 22: AI-Powered CrossFit Coach: Integrating Local Small Language Model and Geospatial Technology for Enhanced Fitness Training. Chapter 23: A Comprehensive Analysis of Image-Based Dietary Assessment Methodologies using Visual Representation.