This book covers the application of game theory, IoT and metaverse related to biomedical and healthcare applications. The book bridges the gap between radiologists and Artificial Intelligence (AI)-driven automated systems by investigating various techniques with a game theoretic approach.
This book focuses on game theory approaches utilized on various domains viz., IoT, blockchain and their applications to biomedical and healthcare services. The book bridges the gap between radiologists and Artificial Intelligence (AI)-driven automated systems by investigating various techniques such as Game Theoretic approach, blockchain technology basically utilized for security and IoT applied on metaverse.
Healthcare Services in the Metaverse: Game Theory, AI, IOT, and Blockchain, identifies the potential areas where game theory and block chain techniques can be harnessed in the metaverse. The book discusses the integration of virtual reality with the augmented reality to identify the new emerging techniques in healthcare to metaverse, where doctors and or patients can see any kind of operation in a virtual reality metaverse. The authors use game theoretical and blockchain approaches to understand healthcare issues. The aim is on utilization of different technologies on metaverse platform towards on health informatics. This book is written to help individuals across the academia, research, and healthcare practitioners as well as for those who work in biomedical, healthcare, IoT, artificial intelligence, metaverse, virtual reality, blockchain and related technologies.
1. Blockchain Technologies in Metaverse.
2. Metaverse Platform Used in Healthcare.
3. Metaverse Platform Used in Different Surgical Operation of Health-care.
4. Computer-aided Detection of Abnormality in Medical Images Using Advanced Metaverse Techniques.
5. Medical Image-based Detection of Brain Tumor Segmentation Using Blockchain and IoT based Techniques.
6. Deep Features to Detect Pulmonary Abnormalities in CXR and CT : Comparative Analysis Using Blockchain. 7.Integration of Medical Imaging with Multi-omics Array Data Using 3D image Using Metaverse.
8. Game Theory Apply on Different Domain of Healthcare.
9. Fake Medicine Identification Using Block-chain Techniques.
10. Application of Metaverse Platform and 3D Imaging.
11. Application of Game Theory and Metaverse to Alzheimer's Disease Classification and Survival Study for Neuroimaging Data.
12. Conclusion and Future Scope.
Dr. Saurav Mallik is currently working as Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, USA. Previously, he worked as Postdoctoral Fellow in Harvard University, MA, USA. Previously, he worked as Postdoctoral Fellow in the Center of Precision Health, Department of School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, and in the Division of Bio-statistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA. He obtained his PhD degree in the Department of Computer Science & Engineering (C.S.E.) from Jadavpur University, Kolkata, India in 2017 while his PhD works carried out in Machine Intelligence Unit (MIU), Indian Statistical Institute (ISI), Kolkata, India.
Dr. Anjan Bandyopadhyay is currently working as Assistant Professor in the Department of School of Computer Science & Engineering in Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. He completed his PhD in the Department of Computer Science & Engineering from National Institute of Technology, Durgapur, West Bengal, India in 2023. He has co-authored more than 30 research publications in various peer-reviewed International Journals, Conferences and Book Chapters. He attended many national and international conferences in India and abroad. His research domains include Cloud Computing, Fog Computing and Algorithmic Game Theory.
Dr. Ruifeng Hu is currently working as Research Fellow at Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA. Previously, he worked as Postdoctoral Fellow in the Center of Precision Health, Department of School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA for three years (2018-2021). His research is focused on the application of multivariate statistics, machine learning, and deep learning to mics data, and bioinformatics data.
Dr. Pawan Kumar Singh is currently an Assistant Professor in the Department of Information Technology, Jadavpur University, Kolkata, West Bengal, India from 2019. Dr. Singh obtained his PhD degree from Jadavpur University in 2018. Previously, he served as assistant professor in Department of Computer Science and Engineering, Techno India-Batanagar, WB, India (2018), Calcutta Institute of Technology (CIT), Uluberia, Howrah, WB, India (2019). Dr. Singh has co-authored more than 100 research papers in various peer-reviewed International Journals, Conferences and BooHis research areas include Pattern Recognition, Computer Vision, Handwriting Recognition, Machine Learning and Artificial Intelligence.
Prof. (Dr.) Soumadip Ghosh is currently serving as a Professor in the Department of Computer Science & Engineering, Sister Nivedita University, Kolkata, India. He obtained his PhD from University of Kalyani, West Bengal, India in 2017. He has more than eighteen years of teaching and research experience. He has co-authored more than 30 research papers, and his research domains are Data Mining, Machine Learning and Deep Learning.
Dr. Sujata Swain is an Assistant Professor in the School of Computer Engineering of Kalinga Institute of Industrial Technology, Orissa, India. She obtained her Ph.D and M. Tech. in the Department of Computer Science and Engineering from Indian Institute of Technology (IIT) Roorkee, India. Previously, she had worked as an Assistant professor at IIMT Engineering College, Meerut Galgotia's College of Engineering and Technology, Greater Noida, India. She has more than 40 publications and her research interests include Web Service Composition, Service-Oriented Computing and Pervasive Computing.
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