Machine and Human Together: Innovating Healthcare with Technology explores the powerful convergence of cutting-edge technology and healthcare delivery. It shows how artificial intelligence, robotics, IoT, blockchain, and digital therapeutics are transforming patient care, diagnosis, and healthcare management worldwide. From drug discovery to hospital operations, the book highlights how machines and humans are collaborating to deliver better outcomes. Readers will gain a deep understanding of telemedicine, wearable technology, genomic medicine, cybersecurity, remote patient monitoring, healthcare chatbots, and other innovations driving the digital health revolution. With a clear focus on human-centered design and ethical considerations, this book equips professionals and learners to navigate the opportunities and challenges of healthcare's technology-driven future. Key Features Explores groundbreaking applications of AI, robotics, IoT, blockchain, and genomics in healthcare. Analyzes real-world use cases across diagnostics, surgery, telehealth, and data management. Applies human-centered design principles to develop usable and ethical healthcare solutions. Integrates interdisciplinary knowledge from medicine, engineering, and data science. Anticipates future trends, challenges, and opportunities shaping digital health.

Optimized Healthcare: Leveraging Technology for Efficiency and Accessibility (Part 2) expands the exploration of transformative healthcare innovations by focusing on mobile health (mHealth), hospital management systems, health information exchange, robotics, telehealth, financial technologies, and workforce training. This volume emphasizes how these advancements work together to improve healthcare accessibility, streamline operations, and ensure sustainability in diverse healthcare settings. Beginning with the rise of mobile health technologies, the book details their role in overcoming geographic barriers, empowering patients, and delivering precision-driven, personalized care. It then examines the optimization of hospital management systems through AI, IoT, cloud computing, and blockchain, highlighting tools for efficiency in patient care, supply chains, financial management, and interoperability. Additional chapters detail health information exchange (HIE) for seamless data sharing, robotics and automation in surgical and caregiving contexts, and the expanding role of telehealth in rural and underserved communities. Key Features: In-depth coverage of mHealth, telehealth, robotics, and financial technologies in healthcare. Practical insights into optimizing hospital management and seamless data exchange. Real-world case studies on technology adoption in diverse global healthcare systems. Focuses on accessibility, patient-centered care, and financial sustainability. Guides on workforce training for effective digital health integration.

Precision Healthcare: Patient Care, Decision Tools, Wearables, Legal and Ethical Issues emphasises the shift from generalised treatment to individualised, data-driven care. The book explores how intelligent decision-support systems, wearable technologies, and AI-enabled tools enhance diagnostics, improve clinical outcomes, and enable personalised patient monitoring. The book offers a comprehensive and future-focused examination of the foundations of precision medicine, its objectives, challenges, policy implications, and the role of data-driven care. Chapters also investigate the transformative impact of the Internet of Medical Things (IoMT), convolutional neural network (CNN)-based respiratory disease detection, wearable health architectures, and AI/ML models for the prediction of neurological, cardiovascular, and metabolic diseases. Further sections highlight advancements in nanomedicine, the emerging influence of large language models in clinical workflows, and the essential legal, ethical, and regulatory frameworks ensuring safe and responsible AI integration in healthcare. Key Features Explains the foundations, policies, and challenges of precision medicine Demonstrates IoMT-driven healthcare models and disease classification frameworks Presents wearables, AI, and ML applications for predictive and personalised care Explores nanomedicine, LLM-enabled clinical tools, and emerging digital therapeutics Integrates technical innovation with ethics, legal compliance, and patient-centric values Provides case studies and interdisciplinary research for real-world applicability

Generative AI in Modern Healthcare brings together research and practical insights on how technologies like machine learning, deep learning, generative AI, and federated learning are transforming healthcare. It explains how these tools are improving diagnosis, treatment planning, and patient care.

The book covers key areas such as personalised medicine, predictive analytics, telemedicine, and AI-based healthcare systems. It also highlights the growing role of AI in medical imaging and diagnostics across fields like radiology, pathology, and cardiology.

In addition, the book explores how AI supports drug discovery, disease prediction, and clinical decision-making, using real-world examples and datasets. It also discusses key challenges, including data quality, bias, privacy, and ethical concerns, as well as secure approaches such as federated learning.

Overall, the book provides a clear understanding of how AI is shaping modern healthcare and improving outcomes.

Key Features

Covers major AI applications in healthcare, including diagnosis and patient care

Explains machine learning, deep learning, and generative AI in simple terms

Includes real-world examples and case studies

Highlights AI use in drug discovery and personalised medicine

Discusses ethics, privacy, and data challenges

Introduces emerging tools like federated learning and large language models