Handbook on augmenting telehealth services using artificial intelligence
1. Artificial intelligence and Healthcare. 1.1 Introduction. 1.2 Pre-processing. 1.3 Radiology's use of artificial intelligence and overcoming its challenges. 1.4 Artificial intelligence and X-rays in Medical Imaging. 1.5 Modelling and Simulation Techniques for Edge AI in Healthcare. Conclusion...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Boca Raton, London, New York
CRC Press
2024
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| Ausgabe: | First edition |
| Schriftenreihe: | Artificial intelligence in smart healthcare systems
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| Schlagworte: |
Artificial intelligence
> Automatic control engineering
> Biomedical engineering
> Biomedizinische Technik
> COM093000
> COM094000
> Communications engineering / telecommunications
> Databases
> Datenbanken
> Datenschutz
> Digital- und Informationstechnologien: Rechtliche Aspekte
> Electrical engineering
> Elektrotechnik
> Engineering: general
> Environmental science, engineering & technology
> Gesundheit, Beziehungen und Persönlichkeitsentwicklung
> Health & personal development
> Ingenieurswesen, Maschinenbau allgemein
> Künstliche Intelligenz
> Legal aspects of IT
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| Zusammenfassung: | 1. Artificial intelligence and Healthcare. 1.1 Introduction. 1.2 Pre-processing. 1.3 Radiology's use of artificial intelligence and overcoming its challenges. 1.4 Artificial intelligence and X-rays in Medical Imaging. 1.5 Modelling and Simulation Techniques for Edge AI in Healthcare. Conclusion and Future Scope. 2. Revolutionizing Healthcare: Impact of Artificial Intelligence in Disease Diagnosis, Treatment and Patient Care. 2.1 Introduction. 2.2 What is Machine Learning, Deep Learning and Natural Language Processing?. 2.3 Timeline For AI Being Used in Healthcare. 2.4 Use of AI in Different Domains of the Healthcare Industry. 2.5 Use of AI Enabled Applications. 2.6 Challenges and Limitations. 2.7 Conclusion. 3. Applications of Healthcare Products Having AI Capability in Disease Diagnosis. 3.1 Introduction. 3.2 Basics of Artificial Intelligence and Machine Learning. 3.3 Clinical Versus AI-Based Disease Diagnosis. 3.4 Deep Learning and disease diagnosis. 3.5 Artificial Intelligence and Radiology. Conclusion. 4. Application of AI for Disease Prediction. 4.1 Introduction. 4. 2 Importance of Disease Prediction. 4.3 Types of AI Algorithms. 4.4 Application of AI in Disease Prediction. 4.5 Dataset. 4.6 Comparison of the AI model with traditional disease prediction methods. 4.7 Conclusion. 5. The Power of AI in Telemedicine: Improving Access and Outcomes. 5.1 Introduction. 5.2 Overview of Telemedicine and AI Technologies. 5.3 AI-Powered Telemedicine Models. 5.4 Case Studies and Real-World Applications. 5.5 Ethical Considerations and Challenges. 5.6 Future Directions and Opportunities. 5.7 Conclusion. 6. AI Ethics and Challenges in Healthcare. 6.1 Introduction. 6.2 AI in medicine. 6.3 Growth factor of AI in health care. 6.4 Ethical issues in AI driven healthcare. 6.5 Legal issues in AI driven healthcare. 6.6 Conclusion. 7. The Future of the Healthcare System: A Meta-Analysis of Remote Patient Monitoring. 7.1 Introduction. 7.2 Android Application. 7.3 How remote patient monitoring works. 7.4 Benefits of remote patient monitoring. 7.5 RPM (Remote Patient Monitoring). 7.6 Controversy. 7.7 Some Organizations That Are Surprising Telemedicine. Conclusion. 8. Artificial Intelligence for Healthcare Delivery System: Future Prospective. 8.1 Introduction. 8.2 Role of sensors in healthcare Sector. 8.3 Role of Software based Mobile Devices in Healthcare Sector. 8.4 Natural Language Processing (NLP). 8.5 Medical imaging technology utilizing AI. 8.6 Role of AI in Cancer Management. 8.7 Remote-controlled Robotic Surgery. 8.8 Precision Medicine. 8.9 Early Sepsis Detection Using Deep Neural Network. 8.10 Impact of AI on Employment in Developed and Developing Nations. 8.11 Dependency of Doctors over Artificial Intelligence in clinical terms. Conclusion. Future Perspectives. 9. Contemporary Practice of Automated Machine Learning For Clinical Repository in Medicinal Field. 9.1 Introduction. 9.2 Automated Machine Learning. 9.3 Automated Machine Learning in Healthcare Industry. 9.4 Challenges and benefits of Working with Clinical Notes. 9.5 Conclusion and Future Scope. 10. Smart innovative medical devices based on Artificial Intelligence. 10.1 Introduction of AI enabled medical devices. 10.2 Development stages of AI-medical devices. 10.3 Regulatory aspects and guideline. 10.4 Merits and Demerits of medical devices. 10.5 Applications. 10.6 Future of AI driven medical devices and Conclusion. 10.7 References. 11. Virtual Consultation: Scope and Application in Healthcare. This handbook offers a cross-disciplinary perspective, models, and innovations in telehealth systems that utilize AI technologies such as Machine Learning, Augmented Reality, Virtual Reality, Big Data Management, and IoT as it discusses various methods for remote care support and services |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xviii, 385 Seiten Illustrationen, Diagramme |
| ISBN: | 9781032385464 978-1-032-38546-4 9781032386805 978-1-032-38680-5 |