In Memory of Ethics: A Dissection of Ethical and Social Issues in Pakistani Professional Healthcare Practice explores the ethical challenges faced within the healthcare sector with a focus on Pakistan. From workplace behaviors to medical procedures, COVID-19 era dilemmas, and broader social health concerns, the book explores the intricate intersection of ethics and healthcare in the region. The book is divided into five sections. Section I covers topics such as workplace behaviors and ethical conducts while section II covers medical procedures, and patient-doctor relationships. Section III addresses the unique ethical challenges brought forth by the COVID-19 pandemic, including guidelines for therapists and the ethics of mandatory vaccinations. Section IV examines the impact of social media on healthcare, gender discrimination, and the ethical considerations surrounding prisoner rehabilitation. The final section offers insightful essays on ethical and social Issues, covering topics like body shaming, free healthcare, and patient privacy. The editors also explore controversial topics, including euthanasia, abortion, and assisted reproductive technology. The key feature of this book is that it provides a comprehensive coverage of diverse ethical dilemmas in healthcare. Furthermore, it is an attempt to give a subjective understanding of healthcare ethics through thought-provoking essays shedding light on contemporary ethical issues in a Pakistani context. The contributors have incorporated real-world examples and case studies to illustrate ethical principles in action. In Memory of Ethics: A Dissection of Ethical and Social Issues in Pakistani Professional Healthcare Practice book is essential reading for anyone interested in understanding complex ethical and social issues and promoting integrity in healthcare practices.

Trauma-informed care is designed to assist persons who have experienced adversity and focuses on change at the clinical and organizational level. Its goals center around prevention, intervention, and treatments that are evidence-based, encourage resilience, and enhance coping. This textbook is designed to give a comprehensive overview of trauma-informed care to students and faculty involved in nursing care programs. Key features: · Explains the skill sets to assess and care for persons who have experienced trauma. · Emphasizes key principles of trauma-informed care · Includes the use of client-centered, person-centered, and resilience-based tools to deal with trauma · Recommends trauma recovery from a positive psychology and post-traumatic growth perspective · Utilizes a caring pedagogy intended to foster resilience and help offset the secondary traumatic stress and compassion fatigue experienced by student and practicing nurses. · Communicates the value of fostering psychological safety, compassion satisfaction, and joy in work · Includes narrative case studies and learning activities in all chapters to help the reader to actively engage with the subject matter. · Presents self-care strategies to enhance physical and emotional well-being.

Prediction in Medicine: The Impact of Machine Learning on Healthcare explores the transformative power of advanced data analytics and machine learning in healthcare. This comprehensive guide covers predictive analysis, leveraging electronic health records (EHRs) and wearable devices to optimize patient care and healthcare planning. Key topics include disease diagnosis, risk assessment, and precision medicine advancements in cardiovascular health and hypertension management. The book also addresses challenges in interpreting clinical data and navigating ethical considerations. It examines the role of AI in healthcare emergencies and infectious disease management, highlighting the integration of diverse data sources like medical imaging and genomic data. Prediction in Medicine is essential for students, researchers, healthcare professionals, and general readers interested in the future of healthcare and technological innovation.

This reference demonstrates the development of a context aware decision-making health informatics system with the objective to automate the analysis of human centric wellness and assist medical decision-making in healthcare. The book introduces readers to the basics of a clinical decision support system. This is followed by chapters that explain how to analyze healthcare data for anomaly detection and clinical correlations. The next two sections cover machine learning techniques for object detection and a case study for hemorrhage detection. These sections aim to expand the understanding of simple and advanced neural networks in health informatics. The authors also explore how machine learning model choices based on context can assist medical professionals in different scenarios. Key Features : -Reader-friendly format with clear headings, introductions and summaries in each chapter -Detailed references for readers who want to conduct further research -Expert contributors providing authoritative knowledge on machine learning techniques and human-centric wellness -Practical applications of data science in healthcare designed to solve problems and enhance patient wellbeing -Deep learning use cases for different medical conditions including hemorrhages, gallbladder stones and diabetic retinopathy Demonstrations of fast and efficient CNN models with varying parameters such as Single shot detector, R-CNN, Mask R-CNN, modified contrast enhancement and improved LSTM models. This reference is intended as a primary resource for professionals, researchers, software developers and technicians working in healthcare informatics systems and medical diagnostics. It also serves as a supplementary resource for learners in bioinformatics, biomedical engineering and medical informatics programs and anyone who requires technical knowledge about algorithms in medical decision support systems.

Resilient Communities: Navigating Public Health Challenges in Developing Nations explores how communities in resource-limited settings can overcome health inequities through resilience, innovation, and collective action. It examines key public health challenges, including communicable and non-communicable diseases, maternal and child health, healthcare access, and water, sanitation, and hygiene (WASH). The book also highlights participatory approaches, disaster preparedness, gender equity, and the role of technology in transforming healthcare delivery. Through real-world case studies, it showcases successful community-driven initiatives and offers practical strategies for strengthening health systems, governance, and leadership. Key Features: - Analyzes public health challenges in developing nations. - Emphasizes community resilience and engagement. - Covers disease prevention, healthcare access, and digital health innovations. - Features case studies and evidence-based strategies. - Advocates for gender equity, sustainable development, and strong health governance.

Advanced Computing Solutions for Healthcare explores the transformative integration of advanced computing technologies into healthcare systems, emphasizing innovation in patient care, diagnostics, and health monitoring. Spanning 22 chapters, it covers topics such as artificial intelligence, machine learning, IoT, data science, and wearable technologies. The book bridges theoretical concepts and practical applications, featuring neuromorphic computing, IoT for healthcare, AI-driven diagnostics, 5G in medicine, augmented reality, and mathematical modeling. It highlights real-world case studies and cutting-edge methodologies, including FPGA-based accelerators, deep learning models for disease classification, and assistive technologies for inclusivity. Key Features: - AI and machine learning applications in diagnostics and personalized care. - IoT, wearable technologies, and 5G for real-time health monitoring. - Data science techniques for predictive analytics and secure data management. - Case studies on emerging technologies like augmented reality and federated learning. - Ethical considerations and challenges in healthcare technology integration.

Securing Healthcare: Leveraging Blockchain for Data Integrity in Healthcare Services comprehensively examines how blockchain technology and smart contracts are reshaping data governance, privacy, and compliance across healthcare systems. Addressing rising concerns around data breaches, regulatory demands, and interoperability challenges, the book explores blockchain's potential to safeguard electronic health records, streamline billing processes, and enhance patient consent mechanisms. Chapters span topics such as medical credential verification, HIPAA compliance, insurance claims, pharmaceutical supply chains, and the role of startups in driving innovation. Emphasis is placed on the integration of smart contracts to automate regulatory compliance and reinforce data integrity within decentralized health ecosystems. Key features: Examines use cases in patient data sharing and consent management Explores smart contract integration for regulatory compliance Analyzes blockchain's role in healthcare billing and credentialing Highlights innovations transforming pharmaceutical transparency Discusses future trends and implementation challenges .

Explore the transformative impact of cutting-edge technologies on modern healthcare systems with Optimized Healthcare: Leveraging Technology for Efficiency and Accessibility (Part 1). With healthcare organizations worldwide facing mounting pressures to improve efficiency, accessibility, and patient outcomes, this book highlights how innovations such as Artificial Intelligence (AI), the Internet of Things (IoT), robotics, blockchain, and digital therapeutics are reshaping clinical care, health management, and patient engagement. Covering topics from electronic health records, telemedicine, and IoT-enabled monitoring to blockchain in health data management, AI-driven diagnostics, and sustainability in healthcare, the book bridges theory with real-world application. Readers gain an in-depth view of how emerging technologies are modernizing patient care, revolutionizing hospital operations, and driving equitable access to health services. Key Features: Comprehensive coverage of emerging technologies transforming healthcare delivery. Insights into AI, IoT, blockchain, and robotics applications in patient care and health management. Focus on sustainability, data analytics, and human-centered design in digital health innovation. Practical guidance on challenges, implementation, and future trends. Multidisciplinary perspectives combining medicine, engineering, policy, and data science.

The Digital Pillbox: Integrating AI, IoT, and Pharma Solutions (Part 1) provides a comprehensive exploration of the intersection of digital technology and pharmaceutical care. The book describes the ways artificial intelligence (AI) and the Internet of Things (IoT) are reshaping the delivery of healthcare, enhancing medication management, and improving patient outcomes. By integrating AI-driven solutions with IoT-enabled devices, the book outlines the role of smart pill dispensers, predictive analytics, and real-time tracking systems in revolutionizing drug administration and adherence. Key Features: Provides exploration of AI, IoT, and blockchain applications in pharmaceuticals. Demonstrates practical case studies showcasing real-world implementations. Discussion of regulatory frameworks, ethical issues, and future trends. Explores personalized medicine, predictive analytics, and telemedicine innovations.

Building on the foundations of Part 1, this volume explores advanced integrations of AI, IoT, and data-driven systems in pharmaceutical logistics, drug lifecycle management, clinical trials, and personalized therapeutics. It emphasizes the emergence of connected ecosystems where devices, data, and decisions interact seamlessly to enhance drug delivery, traceability, and compliance. Chapters cover critical topics such as digital drug development, AI-enabled pharmacovigilance, remote patient monitoring, blockchain-secured supply chains, and ethical frameworks for digital pharma solutions. The book also addresses the challenges of interoperability, cybersecurity, and adapting to global healthcare standards. Key Features: Analyze advanced applications of AI and IoT across the pharmaceutical value chain Examine digital transformation in clinical trials, drug tracking, and e-prescriptions Present case studies on AI-driven decision support and blockchain in pharma logistics Discuss regulatory compliance, cybersecurity, and ethical considerations Explore future trends in connected healthcare and smart medication ecosystems.