This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan UniversityThe coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.Highlights include:Bridging the digital divide with telehealthAI in post-pandemic healthcareNavigating post-pandemic mental health challenges with AIGenomics and personalized medicineEthics, privacy, and security in healthcare informaticsThe book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan UniversityThe coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.Highlights include:Bridging the digital divide with telehealthAI in post-pandemic healthcareNavigating post-pandemic mental health challenges with AIGenomics and personalized medicineEthics, privacy, and security in healthcare informaticsThe book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI’s deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought— “it is a fundamental requirement for responsible AI deployment in healthcare."

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI’s deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought— “it is a fundamental requirement for responsible AI deployment in healthcare."

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan University

The coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.

Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.

Highlights include:

Bridging the digital divide with telehealth AI in post-pandemic healthcare Navigating post-pandemic mental health challenges with AI Genomics and personalized medicine Ethics, privacy, and security in healthcare informatics

The book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan University

The coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.

Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.

Highlights include:

Bridging the digital divide with telehealth AI in post-pandemic healthcare Navigating post-pandemic mental health challenges with AI Genomics and personalized medicine Ethics, privacy, and security in healthcare informatics

The book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI's deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought- "e;it is a fundamental requirement for responsible AI deployment in healthcare."e;

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research.Covering a wide range of topics-from digital health technologies to data analytics and interoperability-it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector's transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation.This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI's deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought- "e;it is a fundamental requirement for responsible AI deployment in healthcare."e;

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research.Covering a wide range of topics-from digital health technologies to data analytics and interoperability-it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector's transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation.This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research. Covering a wide range of topics—from digital health technologies to data analytics and interoperability—it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector’s transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation. This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

In an age where digital transformation is redefining healthcare, this book offers a timely and comprehensive exploration of one of the field’s most dynamic frontiers. This interdisciplinary book brings together leading scholars, clinicians, engineers, and technologists from across the globe to examine how wearable devices and remote monitoring systems are revolutionizing patient care, clinical workflows, and health system performance.From economic and policy implications to machine learning applications, surgical robotics, and patient co-design, the chapters present groundbreaking research and real-world insights. Whether discussing intelligent IoT systems for surgical support or exploring the impact of wearables on healthcare providers’ well-being, this book offers a forward-thinking lens on both the promises and pitfalls of wearable health tech.Highlights include:•    The policy and economic ramifications of wearable integration in healthcare systems.•    Cutting-edge AI and machine learning approaches transforming real-time data into actionable insights.•    The role of wearables in chronic disease management, workforce wellness, and digital co-design.•    Implications for marginalized and disabled populations through inclusive tech innovation.•    Global perspectives on the future of connected health and patient-centered technologies.Written for healthcare leaders, researchers, developers, and policymakers, this essential reference will inspire innovation and inform decision-making in a rapidly evolving digital health landscape.“Wearables are no longer a glimpse of the future—they are reshaping healthcare today.”

In an age where digital transformation is redefining healthcare, this book offers a timely and comprehensive exploration of one of the field’s most dynamic frontiers. This interdisciplinary book brings together leading scholars, clinicians, engineers, and technologists from across the globe to examine how wearable devices and remote monitoring systems are revolutionizing patient care, clinical workflows, and health system performance.From economic and policy implications to machine learning applications, surgical robotics, and patient co-design, the chapters present groundbreaking research and real-world insights. Whether discussing intelligent IoT systems for surgical support or exploring the impact of wearables on healthcare providers’ well-being, this book offers a forward-thinking lens on both the promises and pitfalls of wearable health tech.Highlights include:•    The policy and economic ramifications of wearable integration in healthcare systems.•    Cutting-edge AI and machine learning approaches transforming real-time data into actionable insights.•    The role of wearables in chronic disease management, workforce wellness, and digital co-design.•    Implications for marginalized and disabled populations through inclusive tech innovation.•    Global perspectives on the future of connected health and patient-centered technologies.Written for healthcare leaders, researchers, developers, and policymakers, this essential reference will inspire innovation and inform decision-making in a rapidly evolving digital health landscape.“Wearables are no longer a glimpse of the future—they are reshaping healthcare today.”

This book explores the complex and rapidly evolving internet of things (IOT) and the expanding role of wearable technologies on healthcare. Remote monitoring and wearable devices have become increasingly popular in recent years, enabling continuous tracking of vital signs, activity levels and other health parameters. This can support early detection of potential health issues, facilitate proactive preventive care and allow healthcare providers to monitor patients' conditions remotely. By integrating data from wearables with electronic health records, it is possible to obtain a comprehensive view of a patient's health status. This book is intended primarily for postgraduate students and researchers, but is also suitable for advanced undergraduates across a range of health‑related disciplines. These include computer science (with an emphasis on healthcare informatics), healthcare informatics, data science, biomedical engineering and medical ethics. It is written for readers interested in the intersection of the medical IOT, healthcare and data security. The book also serves as a valuable resource for medical practitioners, healthcare IT professionals, hospital administrators and clinical data analysts. In addition, it will appeal to AI developers, data scientists, cybersecurity analysts and product managers working in healthcare technology.Advancing Healthcare with the Medical Internet of Things offers an overview of cutting‑edge innovations driving smart, responsive and patient‑focused healthcare. The book highlights both the opportunities these devices create and the technological advancements still needed to fully realize their potential. The chapters explore the ethical and legal implications of collecting, storing and using patient data generated by wearable devices, emphasizing the importance of responsible data governance. The book also focuses on hidden biases embedded in IOT systems and their potential to exacerbate existing healthcare disparities, underscoring the need to identify and mitigate these biases to ensure equitable healthcare delivery. In addition, it describes a range of wearable technologies used across global health systems, assessing their advantages and limitations, and therefore equips healthcare providers, policymakers and technologists with a clearer understanding of both the benefits and the risks associated with integrating wearable devices into clinical practice.

This book explores the complex and rapidly evolving internet of things (IOT) and the expanding role of wearable technologies on healthcare. Remote monitoring and wearable devices have become increasingly popular in recent years, enabling continuous tracking of vital signs, activity levels and other health parameters. This can support early detection of potential health issues, facilitate proactive preventive care and allow healthcare providers to monitor patients' conditions remotely. By integrating data from wearables with electronic health records, it is possible to obtain a comprehensive view of a patient's health status. This book is intended primarily for postgraduate students and researchers, but is also suitable for advanced undergraduates across a range of health related disciplines. These include computer science (with an emphasis on healthcare informatics), healthcare informatics, data science, biomedical engineering and medical ethics. It is written for readers interested in the intersection of the medical IOT, healthcare and data security. The book also serves as a valuable resource for medical practitioners, healthcare IT professionals, hospital administrators and clinical data analysts. In addition, it will appeal to AI developers, data scientists, cybersecurity analysts and product managers working in healthcare technology.Advancing Healthcare with the Medical Internet of Things offers an overview of cutting-edge innovations driving smart, responsive and patient-focused healthcare. The book highlights both the opportunities these devices create and the technological advancements still needed to fully realize their potential. The chapters explore the ethical and legal implications of collecting, storing and using patient data generated by wearable devices, emphasizing the importance of responsible data governance. The book also focuses on hidden biases embedded in IOT systems and their potential to exacerbate existing healthcare disparities, underscoring the need to identify and mitigate these biases to ensure equitable healthcare delivery. In addition, it describes a range of wearable technologies used across global health systems, assessing their advantages and limitations, and therefore equips healthcare providers, policymakers and technologists with a clearer understanding of both the benefits and the risks associated with integrating wearable devices into clinical practice.

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan UniversityThe coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.Highlights include:Bridging the digital divide with telehealthAI in post-pandemic healthcareNavigating post-pandemic mental health challenges with AIGenomics and personalized medicineEthics, privacy, and security in healthcare informaticsThe book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan UniversityThe coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.Highlights include:Bridging the digital divide with telehealthAI in post-pandemic healthcareNavigating post-pandemic mental health challenges with AIGenomics and personalized medicineEthics, privacy, and security in healthcare informaticsThe book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI’s deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought— “it is a fundamental requirement for responsible AI deployment in healthcare."

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI’s deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought— “it is a fundamental requirement for responsible AI deployment in healthcare."

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan University

The coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.

Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.

Highlights include:

Bridging the digital divide with telehealth AI in post-pandemic healthcare Navigating post-pandemic mental health challenges with AI Genomics and personalized medicine Ethics, privacy, and security in healthcare informatics

The book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

This book is essential reading for those in healthcare informatics, as well as healthcare administrators, clinicians, and regulators, as they navigate the evolving landscape of healthcare post-pandemic. —Dr. Steven D. Berkshire, professor and director of the Doctor of Health Administration Program, Central Michigan University

The coronavirus disease 2019 (COVID-19) pandemic brought unprecedented challenges to global healthcare systems, revealing vulnerabilities and pushing the boundaries of healthcare informatics. In response, the rapid adoption of digital tools and innovative technologies reshaped the way healthcare is delivered, managed, and analyzed. This transformation has not only revolutionized patient care but also underscored the importance of adopting new strategies to ensure data security, interoperability, and equitable access to healthcare services.

Healthcare Informatics Innovation Post-COVID-19 Pandemic explores the lasting impact of these innovations on the healthcare sector. The book examines the key lessons learned from the pandemic, as well as the challenges and opportunities that have emerged in its wake. It covers a broad range of topics, including telehealth, artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, and examines the critical role each plays in transforming healthcare delivery.

Highlights include:

Bridging the digital divide with telehealth AI in post-pandemic healthcare Navigating post-pandemic mental health challenges with AI Genomics and personalized medicine Ethics, privacy, and security in healthcare informatics

The book’s chapters were written by contributors from diverse academic and professional backgrounds.Together, they share their expertise in healthcare, information technology, and policy. Through their insights, the book provides a comprehensive overview of the current state of healthcare informatics and offers a roadmap for future advancements. This book was written to address the growing recognition that healthcare systems worldwide must be resilient, adaptable, and equipped with cutting-edge tools to navigate future public health crises. As healthcare professionals, academics, policymakers, and technologists work together, it is crucial to share knowledge and collaborate on innovative solutions that can sustain the progress made during the pandemic.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI's deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought- "e;it is a fundamental requirement for responsible AI deployment in healthcare."e;

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research.Covering a wide range of topics-from digital health technologies to data analytics and interoperability-it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector's transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation.This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

Healthcare is fundamentally different from other domains where AI has achieved remarkable success. When an AI system recommends a treatment, suggests a diagnosis, or flags a patient for intervention, lives hang in the balance. Healthcare professionals require more than accurate predictions; they need to understand the reasoning behind those predictions. Explainable AI (XAI) provides the transparency necessary to identify and address algorithmic biases that might perpetuate or exacerbate health disparities.This book addresses this critical challenge by exploring the intersection of healthcare informatics and XAI. It brings together diverse perspectives from clinicians, data scientists, ethicists, and healthcare administrators to examine how transparent and interpretable AI systems can enhance medical practice while maintaining the trust and confidence of both healthcare providers and patients. The book not only showcases technological capabilities but also demonstrates how explainability can bridge the gap between AI innovation and clinical reality.Maintaining a balance between technical rigor and practical accessibility, the book presents detailed discussions of explainability techniques, including SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model- Agnostic Explanations), and causal inference methods. Case studies and examples demonstrate how different XAI techniques can be selected and tailored based on specific requirements. The book also addresses critical implementation challenges.At the threshold of AI's deeper integration into healthcare, the choices made today about transparency and explainability will shape the future of medicine. This book argues that explainability is not a luxury or an afterthought- "e;it is a fundamental requirement for responsible AI deployment in healthcare."e;

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research.Covering a wide range of topics-from digital health technologies to data analytics and interoperability-it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector's transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation.This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

This book addresses the urgent need for AI healthcare insights in a post-pandemic and swiftly progressing world in which the use of advanced health technologies is becoming the norm. It explores the rapidly evolving AI landscape affecting health systems and provides practical, evidence-informed guidance drawn from practice, theory, and research. Covering a wide range of topics—from digital health technologies to data analytics and interoperability—it offers a thorough examination of advancements in these areas, giving readers a comprehensive understanding of the health sector’s transformation. The book goes beyond theory, showcasing practical applications of AI solutions, discussing both advantages and possible disadvantages. Real-world case studies and expert perspectives drawn from recent developments equip readers with actionable insights for implementation in various healthcare settings. With a holistic approach, the book explores not only technological aspects but also ethical considerations, regulatory challenges, and the human impact of digital transformation. This invaluable resource is essential for academics, practitioners, and policymakers in healthcare management, information systems management, healthcare policy, and public health.

In an age where digital transformation is redefining healthcare, this book offers a timely and comprehensive exploration of one of the field’s most dynamic frontiers. This interdisciplinary book brings together leading scholars, clinicians, engineers, and technologists from across the globe to examine how wearable devices and remote monitoring systems are revolutionizing patient care, clinical workflows, and health system performance.From economic and policy implications to machine learning applications, surgical robotics, and patient co-design, the chapters present groundbreaking research and real-world insights. Whether discussing intelligent IoT systems for surgical support or exploring the impact of wearables on healthcare providers’ well-being, this book offers a forward-thinking lens on both the promises and pitfalls of wearable health tech.Highlights include:•    The policy and economic ramifications of wearable integration in healthcare systems.•    Cutting-edge AI and machine learning approaches transforming real-time data into actionable insights.•    The role of wearables in chronic disease management, workforce wellness, and digital co-design.•    Implications for marginalized and disabled populations through inclusive tech innovation.•    Global perspectives on the future of connected health and patient-centered technologies.Written for healthcare leaders, researchers, developers, and policymakers, this essential reference will inspire innovation and inform decision-making in a rapidly evolving digital health landscape.“Wearables are no longer a glimpse of the future—they are reshaping healthcare today.”

In an age where digital transformation is redefining healthcare, this book offers a timely and comprehensive exploration of one of the field’s most dynamic frontiers. This interdisciplinary book brings together leading scholars, clinicians, engineers, and technologists from across the globe to examine how wearable devices and remote monitoring systems are revolutionizing patient care, clinical workflows, and health system performance.From economic and policy implications to machine learning applications, surgical robotics, and patient co-design, the chapters present groundbreaking research and real-world insights. Whether discussing intelligent IoT systems for surgical support or exploring the impact of wearables on healthcare providers’ well-being, this book offers a forward-thinking lens on both the promises and pitfalls of wearable health tech.Highlights include:•    The policy and economic ramifications of wearable integration in healthcare systems.•    Cutting-edge AI and machine learning approaches transforming real-time data into actionable insights.•    The role of wearables in chronic disease management, workforce wellness, and digital co-design.•    Implications for marginalized and disabled populations through inclusive tech innovation.•    Global perspectives on the future of connected health and patient-centered technologies.Written for healthcare leaders, researchers, developers, and policymakers, this essential reference will inspire innovation and inform decision-making in a rapidly evolving digital health landscape.“Wearables are no longer a glimpse of the future—they are reshaping healthcare today.”

This book explores the complex and rapidly evolving internet of things (IOT) and the expanding role of wearable technologies on healthcare. Remote monitoring and wearable devices have become increasingly popular in recent years, enabling continuous tracking of vital signs, activity levels and other health parameters. This can support early detection of potential health issues, facilitate proactive preventive care and allow healthcare providers to monitor patients' conditions remotely. By integrating data from wearables with electronic health records, it is possible to obtain a comprehensive view of a patient's health status. This book is intended primarily for postgraduate students and researchers, but is also suitable for advanced undergraduates across a range of health‑related disciplines. These include computer science (with an emphasis on healthcare informatics), healthcare informatics, data science, biomedical engineering and medical ethics. It is written for readers interested in the intersection of the medical IOT, healthcare and data security. The book also serves as a valuable resource for medical practitioners, healthcare IT professionals, hospital administrators and clinical data analysts. In addition, it will appeal to AI developers, data scientists, cybersecurity analysts and product managers working in healthcare technology.Advancing Healthcare with the Medical Internet of Things offers an overview of cutting‑edge innovations driving smart, responsive and patient‑focused healthcare. The book highlights both the opportunities these devices create and the technological advancements still needed to fully realize their potential. The chapters explore the ethical and legal implications of collecting, storing and using patient data generated by wearable devices, emphasizing the importance of responsible data governance. The book also focuses on hidden biases embedded in IOT systems and their potential to exacerbate existing healthcare disparities, underscoring the need to identify and mitigate these biases to ensure equitable healthcare delivery. In addition, it describes a range of wearable technologies used across global health systems, assessing their advantages and limitations, and therefore equips healthcare providers, policymakers and technologists with a clearer understanding of both the benefits and the risks associated with integrating wearable devices into clinical practice.

This book explores the complex and rapidly evolving internet of things (IOT) and the expanding role of wearable technologies on healthcare. Remote monitoring and wearable devices have become increasingly popular in recent years, enabling continuous tracking of vital signs, activity levels and other health parameters. This can support early detection of potential health issues, facilitate proactive preventive care and allow healthcare providers to monitor patients' conditions remotely. By integrating data from wearables with electronic health records, it is possible to obtain a comprehensive view of a patient's health status. This book is intended primarily for postgraduate students and researchers, but is also suitable for advanced undergraduates across a range of health related disciplines. These include computer science (with an emphasis on healthcare informatics), healthcare informatics, data science, biomedical engineering and medical ethics. It is written for readers interested in the intersection of the medical IOT, healthcare and data security. The book also serves as a valuable resource for medical practitioners, healthcare IT professionals, hospital administrators and clinical data analysts. In addition, it will appeal to AI developers, data scientists, cybersecurity analysts and product managers working in healthcare technology.Advancing Healthcare with the Medical Internet of Things offers an overview of cutting-edge innovations driving smart, responsive and patient-focused healthcare. The book highlights both the opportunities these devices create and the technological advancements still needed to fully realize their potential. The chapters explore the ethical and legal implications of collecting, storing and using patient data generated by wearable devices, emphasizing the importance of responsible data governance. The book also focuses on hidden biases embedded in IOT systems and their potential to exacerbate existing healthcare disparities, underscoring the need to identify and mitigate these biases to ensure equitable healthcare delivery. In addition, it describes a range of wearable technologies used across global health systems, assessing their advantages and limitations, and therefore equips healthcare providers, policymakers and technologists with a clearer understanding of both the benefits and the risks associated with integrating wearable devices into clinical practice.