Chapter 3 Blockchain-empowered metaverse healthcare systems and applications
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S.C. Vetrivel
Abstract
The integration of artificial intelligence (AI) and machine learning (ML) with blockchain technology has the potential to revolutionize diagnostics and treatment within the metaverse. The metaverse, a virtual reality space where individuals interact with computer-generated environments and other users, offers a unique platform for healthcare innovation. This chapter explores how the integration of AI, ML, and blockchain can enhance diagnostics and treatment within the metaverse. AI and ML algorithms can analyze vast amounts of data and identify patterns that may not be apparent to human observers. In the context of the metaverse, AI algorithms can analyze user behavior, physiological data, and virtual environment interactions to provide valuable insights into a user’s health status. By leveraging blockchain technology, these insights can be securely stored and shared across the metaverse, ensuring data integrity and privacy. The use of AI and ML in the metaverse can enable improved diagnostics by detecting early signs of diseases and providing personalized recommendations for treatment. For example, AI algorithms can monitor a user’s virtual interactions and detect subtle changes in behavior that may indicate mental health issues. By analyzing speech patterns, facial expressions, and physiological responses, AI can provide real-time feedback and connect users with appropriate mental health resources.
Abstract
The integration of artificial intelligence (AI) and machine learning (ML) with blockchain technology has the potential to revolutionize diagnostics and treatment within the metaverse. The metaverse, a virtual reality space where individuals interact with computer-generated environments and other users, offers a unique platform for healthcare innovation. This chapter explores how the integration of AI, ML, and blockchain can enhance diagnostics and treatment within the metaverse. AI and ML algorithms can analyze vast amounts of data and identify patterns that may not be apparent to human observers. In the context of the metaverse, AI algorithms can analyze user behavior, physiological data, and virtual environment interactions to provide valuable insights into a user’s health status. By leveraging blockchain technology, these insights can be securely stored and shared across the metaverse, ensuring data integrity and privacy. The use of AI and ML in the metaverse can enable improved diagnostics by detecting early signs of diseases and providing personalized recommendations for treatment. For example, AI algorithms can monitor a user’s virtual interactions and detect subtle changes in behavior that may indicate mental health issues. By analyzing speech patterns, facial expressions, and physiological responses, AI can provide real-time feedback and connect users with appropriate mental health resources.
Chapters in this book
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
Chapters in this book
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
