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Generative AI Techniques for Sustainability in Healthcare Security
In a world of constant change, sustainability and technology emerge as pivotal elements in healthcare. Generative artificial intelligence (AI) presents the capabilities of more accurate diagnoses, personalized treatment plans, and drug discovery, while certain operations in healthcare, such as managing relationships with healthcare systems often necessitate a human touch, these processes can be augmented by generative AI. Sustainability and health security are becoming increasingly important. The relationship between sustainability and health security is significant, as environmental factors such as air pollution, climate change, and access to green spaces can all affect human health. Genera...
Advances in Computational Intelligence for the Healthcare Industry 4.0
In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of...
Artificial Intelligence Transformations for Healthcare Applications: Medical Diagnosis, Treatment, and Patient Care
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 todays 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...
Digital Twins and Healthcare: Trends, Techniques, and Challenges
The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These t...
Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems
As the demand for advanced technologies to revolutionize patient care intensifies, the medical industry faces a pressing need to confront challenges hindering the assimilation of AI-enhanced healthcare systems. Issues such as data interoperability, ethical considerations, and the translation of AI advancements into practical clinical applications pose formidable hurdles that demand immediate attention. It is within this context of challenges and opportunities that the book, Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems promises to pave the way for a transformative era in healthcare. The book serves as a comprehensive guide for academic scholars, researchers, and healthcare professionals navigating the dynamic landscape of data-driven, AI-enhanced healthcare. By showcasing the latest advancements, the book empowers its readers to not only comprehend the existing frontiers in data sciences and healthcare technologies but also to actively contribute to overcoming obstacles. Through detailed case studies and practical guidance, the publication equips its audience with the skills necessary to implement AI in various clinical settings.
Technologies for Sustainable Healthcare Development
In contemporary healthcare, Industry 5.0 technologies present a paradoxical challenge and opportunity. The rapid integration of Cyber Physical Systems, Cloud Computing, Internet of Things, Artificial Intelligence, Smart Factories, and Cognitive Computing has ushered in unprecedented transformations, yet it has concurrently given rise to critical vulnerabilities within healthcare systems. As sensitive patient data becomes increasingly digitized, the specter of cybersecurity threats looms larger than ever. The book, titled "Technologies for Sustainable Healthcare Development," undertakes the crucial task of addressing this pressing concern. Focused on Cybersecurity and Data Science Innovations...
Revolutionizing Healthcare Treatment With Sensor Technology
Traditional patient care and treatment approaches often lack the personalized and interactive elements necessary for effective healthcare delivery. This means that the healthcare industry must find innovative solutions to improve patient outcomes, enhance rehabilitation processes, and optimize resource utilization. There is a gap between the traditional approach and the need for innovation that highlights the importance of a comprehensive understanding of emerging technologies, including Kinect Sensor technology, and the potential to transform healthcare practices with this tech. Revolutionizing Healthcare Treatment With Sensor Technology addresses this critical need by thoroughly exploring ...
AI-Driven Alzheimer's Disease Detection and Prediction
Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.
Modernizing Maternal Care With Digital Technologies
In the ever-evolving landscape of maternal healthcare, expectant mothers face a myriad of challenges, from pregnancy complications to postpartum care. Traditional approaches often fail to provide timely and personalized interventions, leading to suboptimal outcomes for both mother and child. The lack of practical tools and strategies to address these complexities underscores the pressing need for innovative solutions that can revolutionize maternal care. Modernizing Maternal Care With Digital Technologies leads the way, offering a comprehensive solution that harnesses the power of modern technology and soft computing techniques to foster environments that improve maternal patient outcomes. This pioneering book delves into the transformative role of artificial intelligence (AI), data analytics, and wearable devices in reshaping maternal care. The book presents a paradigm shift in how expectant mothers can be supported throughout their pregnancy journey by highlighting the significance of predictive modeling and real-time monitoring.
Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0
The healthcare industry is increasingly complex, demanding personalized treatments and efficient operational processes. Traditional research methods need help to keep pace with these demands, often leading to inefficiencies and suboptimal outcomes. Integrating digital twin technology presents a promising solution to these challenges, offering a virtual platform for modeling and simulating complex healthcare scenarios. However, the full potential of digital twins still needs to be explored mainly due to a lack of comprehensive guidance and practical insights for researchers and practitioners. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 is not just a the...
