Transforming Healthcare by Jain, Ankush; Srivastava, Vishal; Singal, Gaurav;

Rövid leírás:

This comprehensive volume explores cutting-edge technologies, groundbreaking methodologies, and insightful ethical considerations. It brings together leading minds and research across diverse domains, offering readers a glimpse into the future of healthcare.

Hosszú leírás:

This comprehensive volume explores cutting-edge technologies, groundbreaking methodologies, and insightful ethical considerations. It brings together leading minds and research across diverse domains, offering readers a glimpse into the future of healthcare. From leveraging AI in diagnostics and personalized treatments to advancing telemedicine and remote patient monitoring, the text addresses real-world challenges and opportunities in the rapidly evolving healthcare industry.

Key features:

• Innovative approaches to early disease detection, including Alzheimer’s and cancer, using machine learning and deep learning techniques.


• State-of-the-art applications of design thinking, meta-heuristics, and federated learning in healthcare.


• Ethical perspectives on the use of AI technologies and their impact on businesses and patient care.


• A deep dive into the role of IoT, NLP, and AI-driven image processing in revolutionizing healthcare delivery.


• Generalized models analyzing trade credits and their implications for healthcare supply chains.

Whether you're a researcher, healthcare professional, or technology enthusiast, this book serves as an invaluable resource for understanding and shaping the future of health technologies. Packed with diverse perspectives and actionable insights, it’s a must-read for anyone passionate about making a difference in healthcare.

Tartalomjegyzék:

1. Innovating Health: Design Thinking in Emerging Technologies. 2. Next-Gen Health Analytics: Meta-heuristic Bi-clustering of Gene Expression Data with K-means. 3. Uncovering methods for early Alzheimer Diagnosis using Machine Learning and Deep Learning. 5. A Comparative Study on Transfer Learning Models and Ensemble Transfer Learning Models on Multi-Class Skin Cancer Classification. 6. Benefits and Drawbacks of Using AI Technologies in Healthcare Businesses: An Ethical Perspective. 8. Analysis and Predicting Sector Data: The Role of Health News, Telemedicine, and Remote Patient Monitoring. 9. A Generalized Model on the Effect of Trade Credits on Healthcare Items under Multivariate Demand Based Production with Time Dependent Deterioration and Partial Backlogging. 10. AI and NLP based system for Early Detection of Malignant Cells of Brain through Image Processing paving way for Personalized Treatment Strategies. 11. Advancing Healthcare AI with Federated Learning. 12. A Systematic Review of Applications, Challenges, Data Collection, and Academic Research in Healthcare Using IoT. 13. Revolutionizing Healthcare: Cutting-Edge Technologies and their Applications. 14. Speech Emotion Recognition in Mental Health: A Novel Approach Using Machine Learning.