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

Experts in Medicine are under new pressures of advancing their studies while also reducing the impact they leave on the environment. Researchers within the fields of bio-neuro informatics, healthcare, engineering, and medical sciences require a dynamic platform that bridges the realms of academia, science, industry, and innovation. Green AI-Powered Intelligent Systems for Disease Prognosis facilitates a crossroads for a diverse audience interested in these two seldom coalesced concepts. Academicians, scientists, researchers, professionals, decision-makers, and even aspiring scholars all find a space to contribute, collaborate, and learn within the platform that this book provides. The book's thematic coverage is unequivocally compelling; by exploring the intersections of bio-neuro informatics, healthcare, engineering, and medical sciences, it captures the spirit of interdisciplinary research. It delves into well-established domains while also casting a spotlight on emerging trends that have the potential to reshape our understanding of these fields. Two prominent tracks form the backbone of the book's content. The first covers the Bioinformatics and Data Mining of Biological Data (BiDMBD), and unravels the intricacies of biomedical computation, signal analysis, clinical decision support, and health data mining. This approach holds a treasure trove of insights into the mechanisms of health data acquisition, clinical informatics, and the representation of healthcare knowledge. The second covers Biomedical Informatics and is a symposium of computational modeling, genomics, and proteomics. Here, the fusion of data science with medical sciences takes center stage.

As the world grapples with pressing environmental challenges, the need for sustainable solutions has never been more urgent. From climate change to resource depletion, our planet faces unprecedented threats that require immediate action. Revolutionizing Automated Waste Treatment Systems: IoT and Bioelectronics emerge as a beacon of hope, offering comprehensive insights and practical guidance to address these critical issues. By delving into the principles and applications of green technologies, this book presents a roadmap towards a greener, more sustainable future. Recognizing the essential role that green technologies play in mitigating environmental degradation, this book emphasizes concepts such as smart technologies, bioelectronics, and the internet of things. It also illustrates how these innovations can be leveraged to create a more sustainable world. Readers will be educated on the importance of adopting these technologies, and the book provides actionable strategies for implementation. Use this impressive resource to grasp a more holistic approach to environmental sustainability, from designing green infrastructure to managing water resources.

Artificial intelligence (AI) has emerged as a transformative force across various domains, revolutionizing the way we perceive and address challenges in healthcare. The convergence of AI and healthcare holds immense promise, offering unprecedented opportunities to enhance medical diagnosis, treatment, and patient care. In today’s world, the intersection of AI and healthcare stands as one of the most promising frontiers for innovation and progress. Artificial Intelligence Transformations for Healthcare Applications: Medical Diagnosis, Treatment, and Patient Care embodies this convergence, offering a comprehensive exploration of how AI is revolutionizing various aspects of healthcare delivery. At its core, this book addresses the urgent need for more effective and efficient healthcare solutions in an increasingly complex and data-rich environment. Covering topics such as chronic disease, image classification, and precision medicine, this book is an essential resource for healthcare professionals, medical researchers, AI and machine learning specialists, healthcare administrators and executives, medical educators and students, biomedical engineers, healthcare IT professionals, policy makers and regulators, academicians, and more.

"This book studies the application of AI tools on healthcare such as machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, and implementation of healthcare solutions, exploring many healthcare research topics such as disease diagnosis and assistance, diet proposal, physical and psychological assistance, and drug prescription and trucking"--

In the context of an ever-changing technological world, it is crucial to prioritize the cultivation of sustainability and environmental consciousness. Adopting an interdisciplinary perspective, this handbook facilitates the integration of technology and sustainability by leveraging insights from many fields such as engineering, environmental science, economics, and sociology. The primary objective of this handbook is to provide a comprehensive analysis of the complex relationship between technology and the environment. Handbook of Technological Sustainability: Innovation and Environmental Awareness includes recent and diverse case studies from a global perspective and demonstrates the utilization of technology to achieve sustainable development across several sectors, such as energy, agriculture, transportation, and urban planning. It explores innovative technologies emphasizing state-of-the-art and developing technologies, including renewable energy, circular economy practices, smart cities, and artificial intelligence-driven sustainability solutions. The handbook also examines the impact of laws, regulations, and international agreements on the advancement or impediment of technological sustainability. Written to be used as a reference, this handbook highlights the ethical and moral quandaries linked to technological sustainability analyzing various topics of significance, including environmental justice, privacy implications in smart technology, and the ramifications of artificial intelligence on employment and society. It provides practical methodologies and recommendations for individuals, enterprises, and governmental entities to adopt and integrate sustainable technologies effectively and furnish readers with a comprehensive guide for transitioning towards a more sustainable future. As it showcases perspectives from technologists, sustainability professionals, and policymakers that have the potential to provide a range of opinions and practical insights derived from real-world experiences, this handbook is a book for all individuals, corporations, governments, researchers, and anyone seeking to harness technology to advance sustainability and effectively tackle the multifaceted issues posed by our dynamic global landscape.