Driving Smart Medical Diagnosis Through Ai Powered Technologies And Applications

Academic scholars face the daunting challenge of keeping pace with the rapid evolution of innovative technologies. The emergence of AI-driven solutions, deep learning frameworks, and medical robotics introduces a complex terrain, demanding in-depth understanding and analysis. As scholars navigate the intricacies of patient hate speech detection, cardiovascular diseases AI-CDSS, and the revolution in medical diagnostics, a pressing need arises for comprehensive insights that bridge the gap between theoretical knowledge and practical applications. Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications serves as a solution in this era of transformative healthcare and addresses these challenges head-on. It unravels the complexities surrounding the implementation of AI in healthcare, offering in-depth discussions on the latest breakthroughs. From unraveling the mysteries of AI-driven cataract detection to exploring the implications of decentralized mammography classification, the book is a valuable resource that equips scholars with the knowledge to navigate this innovative landscape.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

In the intricate tapestry of nature, the potential of kitchen spice seeds remains largely untapped, despite their rich history as sources of natural compounds with diverse benefits. The scientific community faces a challenge in fully comprehending and harnessing the phytochemical, ethnobotanical, and pharmacological dimensions of these seeds, which hold promise in medicine but play pivotal roles in cultural, historical, and culinary spheres. Therapeutic and Pharmacological Applications of Ethnobotany is an all-encompassing compendium meticulously crafted to bridge these knowledge gaps. By presenting a synthesis of phytochemical analysis, ethnobotanical insights, pharmacological studies, botanical descriptions, industrial and culinary applications, biogenic synthesis, and innovative uses, this book provides a holistic exploration of kitchen spice seeds. Tailored for researchers, scientists, botanists, pharmacologists, ethnobotanists, and culinary experts, it serves as a beacon guiding readers through the scientific intricacies and cultural significances of these seeds, unlocking a wealth of knowledge that transcends disciplinary boundaries.

In the ancient world, health seekers traversed vast distances to pursue well-being. Fast forward to the 21st century, and the concept of medical tourism has evolved into a global industry worth billions of dollars. The burgeoning demand for quality healthcare has pushed traditional boundaries, necessitating a more sophisticated and interconnected healthcare ecosystem. Integrating Artificial Intelligence (AI) into medical practices empowers individuals to actively manage their health while providing healthcare practitioners with invaluable insights for tailored patient care. Impact of AI and Robotics on the Medical Tourism Industry delves into the transformative impact of AI and robotics on this dynamic sector. It explores how AI can encourage and assist patients in their health plans while augmenting healthcare practitioners' capabilities to utilize specific patient data to offer unique guidance. It dissects real-world examples, such as Cleveland Clinic Abu Dhabi's integration of robotic surgery, showcasing how these technologies revolutionize traditional medical practices.

The rise of modern antimicrobial drug resistance has evolved into a pressing global health crisis, challenging the very foundation of our ability to combat infectious diseases. The overuse and accessibility of antibiotics, particularly in emerging nations, have given rise to resilient "superbugs," rendering common medications ineffective. This escalating challenge poses a significant threat to public health and leads to heightened healthcare costs, prolonged patient stays, and increased mortality rates. As communities grapple with the urgent need for a coordinated response, a comprehensive understanding of antimicrobial drug resistance and innovative strategies becomes paramount. Frontiers in Combating Antibacterial Resistance: Current Perspectives and Future Horizons is meticulously crafted for academic scholars, researchers, and healthcare professionals. It addresses this critical issue head-on and serves as a beacon of knowledge and a solution-oriented guide. With a focus on elucidating the mechanisms behind antimicrobial drug resistance and exploring emerging therapeutic targets, the book presents an in-depth analysis of the problem. It spans environmental, genetic, and climatic factors influencing resistance, delving into cutting-edge technologies and sustainable strategies for prevention. By offering a holistic view of the issue and proposing evidence-based solutions, the book is an indispensable resource for those seeking to navigate the complex landscape of antimicrobial drug resistance.

In the field of healthcare technology, the Internet of Medical Things (IoMT) stands at the forefront of progress, revolutionizing patient care through advanced monitoring and treatment modalities. However, this digital transformation brings forth a new challenge— the vulnerability of sensitive medical data to cyber threats. Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) examines ways to fortify IoMT against potential breaches through the exploration of these trust architectures. Delving deep into data privacy technologies, the book examines the implications of regulatory frameworks such as GDPR, HIPAA, and cybersecurity law. It assesses traditional security methods and considers innovative approaches, offering insights into certificate generation, digital identification, and the optimization of network protocols for secure data transmission.Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) illuminates the path forward for IoMT security. Its objectives are multi-faceted: from unraveling the intricacies of the health chain to dissecting the role of lightweight cryptographic key agreement mechanisms in safeguarding medical data. The book grapples with the challenges and advantages of implementing compact cryptographic techniques in healthcare, particularly within the decentralized framework of IoMT. By exploring the potential of Federated Learning (FL) in bolstering privacy and improving healthcare outcomes, the book aims to equip researchers, healthcare professionals, and IT experts with valuable knowledge. Through real-world case studies, it endeavors to pave the way for a future where security and efficiency seamlessly integrate in IoMT.

Artificial intelligence (AI) technology has been very successful across fields such as healthcare, security, precision agriculture, smart city, and autonomous driving and promises numerous benefits for social development, economic growth, wellbeing management, and human healthcare. Various intelligent healthcare applications have been created in order to assist patient healthcare and must be studied further. AI Applications for Disease Diagnosis and Treatment provides the current advances and applications of artificial intelligence applications in healthcare such as disease diagnosis, diet proposal, drug prescription and tracking, and physical and psychological assistance. Covering topics such as assistive healthcare, robotics, and machine learning, it is ideal for healthcare professionals, researchers, data analysts, academicians, practitioners, scholars, instructors, and students.

In the wake of the digital healthcare revolution, a critical challenge has emerged: the lack of a comprehensive understanding stemming from fragmented research. Despite the industry's meteoric rise, existing literature often compartmentalizes insights, neglecting the intricate multi-sector collaborations that fuel its progress. This gap hinders scholars and industry professionals, leaving them with a myopic view of the digital healthcare landscape. The urgent need for a holistic exploration has never been more apparent. Multi-Sector Analysis of the Digital Healthcare Industry is a groundbreaking book that will uncover the complexities of digital healthcare with a panoramic lens. This carefully curated collection of cross-functional chapters is a beacon guiding academics and industry specialists through the difficulties of the industry's past, present, and future. With experts from fields spanning medicine, technology, business, and regulatory sectors, this book addresses the limitations of current research but serves as a compass for those seeking a more profound comprehension of digital healthcare's collaborative dynamics.