| Description |
1 online resource (431 p.) |
| Contents |
Cover -- Title Page -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgment -- List of Contributors -- List of Figures -- List of Tables -- List of Abbreviations -- Chapter 1: Healthcare 4.0: A Systematic Review and Its Impact Over Conventional Healthcare System -- 1.1: Introduction -- 1.1.1: Application scenarios of healthcare 4.0 -- 1.1.2: The architecture of healthcare 4.0 -- 1.1.3: Requirements and characteristics of healthcare 4.0 -- 1.2: Evolution of Healthcare -- 1.3: Need of Healthcare 5.0 -- 1.4: Advances in the Healthcare Industry |
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1.4.1: M-Healthcare -- 1.4.2: Healthcare data of patients -- 1.4.3: IoT and healthcare -- 1.4.4: Blockchain technology and healthcare -- 1.4.5: Big data analytics and healthcare -- 1.5: Telemedicine Services -- 1.5.1: Big data and IoT for healthcare 4.0 -- 1.5.2: Blockchain and healthcare 4.0 -- 1.5.3: AI and healthcare 4.0 -- 1.5.4: Cyber-physical system and healthcare 4.0 -- 1.5.5: Smart medical devices -- 1.6: Opportunities and Challenges Involved in Healthcare -- 1.7: Future Scope and Trends -- 1.8: Conclusion -- 1.9: Acknowledgment -- 1.10: Funding -- 1.11: Conflict of Interest -- References |
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Chapter 2: Data Imaging, Clinical Studies, and Disease Diagnosis using Artificial Intelligence in Healthcare -- 2.1: Introduction -- 2.1.1: Classifications of artificial intelligence -- 2.1.1.1: Machine learning: Deep learning and neural network -- 2.1.1.2: Rule-based expert systems -- 2.1.1.3: Physical robots and software robotics -- 2.2: Machine Learning for Typical Biomedical Data Types -- 2.2.1: Data from multiple omics -- 2.2.2: Integration based on data -- 2.2.3: Incorporating models -- 2.2.4: Data on behavior -- 2.2.5: Data from video and conversations -- 2.2.6: Mobile sensor data |
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2.2.7: Data on the environment -- 2.2.8: Pharmaceutical research and development data -- 2.2.8.1: Chemical compounds -- 2.2.8.2: Clinical trials -- 2.2.9: Unintentional reports -- 2.2.10: Literature in biomedicine data -- 2.3: Application of AI -- 2.3.1: Biomedical information processing -- 2.3.2: AI for living support -- 2.3.3: Biomedical research -- 2.3.4: Medicine -- 2.3.5: Cancer and miscellaneous -- 2.4: Assessment of AI Applications in Healthcare -- 2.4.1: Phase 0 -- 2.4.2: Phase 1 -- 2.4.3: Phase 2 -- 2.4.4: Phase 3 -- 2.4.5: Phase 4 |
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2.5: Artificial Intelligence's Challenges in the Use of Pharmaceutical R&D Data -- 2.6: Future Directions for AI in Healthcare -- 2.6.1: Analytical integration -- 2.6.2: Transparency in models -- 2.6.3: Model security -- 2.6.4: Learning that is federated -- 2.6.5: Data errors -- 2.7: Conclusion -- 2.8: Acknowledgment -- 2.9: Funding -- 2.10: Conflicts of Interest -- References -- Chapter 3: Leveraging Artificial Intelligence in Patient Care -- 3.1: Introduction -- 3.2: Advancement in Artificial Intelligence -- 3.2.1: AI spring: artificial intelligence's inception |
| Summary |
This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research |
| Notes |
Description based upon print version of record |
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3.2.2: AI summer and winter: Artificial intelligence's highs and lows |
| Form |
Electronic book
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| Author |
Chilamkurti, Naveen
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Sundram, Sonali
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Dhanaraj, Rajesh Kumar
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Balusamy, Balamurugan
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| ISBN |
9781000847024 |
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1000847020 |
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