Revolutionizing Healthcare Systems with Next-Generation Technologies: The Role of Artificial Intelligence, Cloud Infrastructure, and Big Data in Driving Patient-Centric Innovation
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https://doi.org/10.70593/978-81-988918-5-3
Keywords:
Artificial Intelligence , Healthcare, Cloud Computing, Big Data Analytics, Medicine, Predictive Modeling, Clinical Decision Support SystemsSynopsis
In the ever-evolving landscape of global healthcare, the convergence of Artificial Intelligence (AI), Cloud Infrastructure, and Big Data is reshaping how care is delivered, diseases are detected, and patient outcomes are improved. This book, Revolutionizing Healthcare Systems with Next-Generation Technologies: The Role of Artificial Intelligence, Cloud Infrastructure, and Big Data in Driving Patient-Centric Innovation, seeks to explore how these transformative technologies are enabling a shift from reactive to proactive, from generalized to personalized, and from fragmented to integrated healthcare systems. The vision for this work emerged from the growing realization that traditional models of care are no longer sufficient in addressing the complexities of modern medicine. Healthcare providers today must respond to an expanding population, an explosion of health data, and an increasing demand for more accessible, affordable, and individualized care. AI-driven diagnostics, predictive analytics powered by big data, and scalable cloud platforms have become essential tools in this transformation—making healthcare not only smarter but also more compassionate and responsive to individual needs.
This book is designed for a wide audience—from researchers, practitioners, and policymakers to technology innovators and students. It offers a comprehensive view of how next-gen technologies are being deployed across healthcare sectors including clinical decision-making, hospital operations, disease surveillance, remote patient monitoring, and precision medicine. It highlights successful implementations, emerging challenges, and ethical considerations, while emphasizing the need for a human-centered approach in tech-driven care. As we look toward the future, this work serves as both a roadmap and a call to action—urging stakeholders to embrace innovation, build interoperable systems, and ensure that the benefits of these technologies reach every patient, regardless of geography or income. With thoughtful collaboration between technologists, clinicians, and communities, we believe that the next revolution in healthcare is not only possible—it is already underway.
Chapters
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Understanding the digital transformation landscape in modern healthcare systems
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Enhancing clinical decision-making using artificial intelligence applications
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Developing machine learning algorithms for improved diagnosis and prognosis
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Architecting cloud-based infrastructure for scalable and secure health data storage
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Establishing best practices for securing sensitive healthcare information in the cloud
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Utilizing big data analytics for real-time patient monitoring and risk prediction
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Predictive models for early detection of diseases and managing public health crises
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Building end-to-end data engineering solutions for medical research and analysis
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Telemedicine and remote patient management through emerging digital platforms
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Integrating advanced technologies into existing healthcare systems and workflows
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Cross-disciplinary learnings from agricultural technologies for healthcare data management
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Exploring the future of artificial intelligence, cloud, and data-driven innovation in healthcare delivery
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Published
6 June 2025
Copyright (c) 2025 Karthik Chava
Details about the available publication format: E-Book
E-Book
ISBN-13 (15)
978-81-988918-5-3
Details about the available publication format: Book (Paperback)
Book (Paperback)
ISBN-13 (15)
978-81-988918-7-7
How to Cite
Chava, K. . (2025). Revolutionizing Healthcare Systems with Next-Generation Technologies: The Role of Artificial Intelligence, Cloud Infrastructure, and Big Data in Driving Patient-Centric Innovation. Deep Science Publishing. https://doi.org/10.70593/978-81-988918-5-3
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