In recent years, Artificial Intelligence (AI) has revolutionized medical radiology, allowing rapid and accurate analysis of large volumes of data and the detection of imperceptible patterns in the human eye. This book aims to be a source of knowledge and inspiration, contributing to the advancement of medical radiology through artificial intelligence. It offers theoretical and practical knowledge to transform clinical practice and improve the diagnosis and treatment of illnesses, positioning readers to take advantage of opportunities in this constantly evolving field.

This reference text presents the usage of artificial intelligence in healthcare and discusses the challenges and solutions of using advanced techniques like wearable technologies and image processing in the sector. Features: Focuses on the use of artificial intelligence (AI) in healthcare with issues, applications, and prospects Presents the application of artificial intelligence in medical imaging, fractionalization of early lung tumour detection using a low intricacy approach, etc Discusses an artificial intelligence perspective on wearable technology Analyses cardiac dynamics and assessment of arrhythmia by classifying heartbeat using electrocardiogram (ECG) Elaborates machine learning models for early diagnosis of depressive mental affliction This book serves as a reference for students and researchers analyzing healthcare data. It can also be used by graduate and post graduate students as an elective course.

The field of medical imaging is rapidly evolving, with new technologies and techniques constantly emerging. However, this fast-paced advancement brings challenges such as the complexity of imaging modalities, the need for continuous education and training, and the integration of emerging technologies like AI and robotics into existing healthcare systems. Healthcare professionals and technology enthusiasts often need help to keep pace with these changes and may feel overwhelmed by the vast amount of information and possibilities in the field. Enhancing Medical Imaging with Emerging Technologies offers a comprehensive solution to these challenges. By providing a thorough introduction to medical imaging systems, including the fundamentals of system theory and image processing, the book serves as a foundational resource for understanding the complex world of medical imaging. It covers various imaging modalities, from conventional camera systems to advanced techniques like magnetic resonance imaging and optical coherence tomography, offering readers a holistic view of the field. This book is a valuable resource that inspires hope, sparks curiosity, and paints a vivid picture of the limitless potential of medical imaging.

Establishing the means to improve performance in healthy, clinical, and military populations has long been a focus of study in the psychological and brain sciences. However, a major obstacle to this goal is generating individualized performance phenotypes that allow for the design of interventions that are tailored to the specific needs of the individual. Recent developments in artificial intelligence (AI) have qualified for the development of precision approaches that consider individual differences, allowing, for example, the establishment of individualized training, preparation, and recuperation programs optimal for an individual’s cognitive and biological phenotype. Corollary developments in AI have proven that combining domain expertise and stakeholder insights can considerably improve AI’s quality, performance, and dependability in the psychology and brain sciences. Recent Developments in Machine and Human Intelligence studies original empirical work, literature reviews, and methodological papers that establish and validate precision AI methods for human performance optimization with a focus on modeling individual differences via state-of-the-art computational methods and investigating how domain expertise and human judgment can improve the performance of AI methods. The topics are crafted in such a way as to cover all the areas of artificial and human intelligence that require AI for further development. This book contains algorithms and techniques that are explained with the help of developed source code and encompasses the readiness and needs for advancements in managing yet another pandemic in the future. It is designed for academicians, scientists, research scholars, professors, graduates, undergraduates, and students.

The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians.

The business world today is changing at a breakneck pace. Traditional management practices need help keeping up with the uncertainties and complexities of the digital age. Leaders face a lot of pressure to innovate, adapt, and drive transformative change within their organizations. However, they need more than just conventional wisdom to navigate this terrain. A deep understanding of emerging technologies like artificial intelligence (AI) and their practical applications in management is essential. Generative AI for Transformational Management offers a compelling solution to these challenges. This book provides a roadmap for leveraging AI to drive organizational transformation by exploring the intersection of generative AI and visionary leadership. By examining real-world case studies and practical applications, readers can learn how AI can be integrated into leadership practices to promote innovation and proactive decision-making and effectively navigate the complexities of the digital age.

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 in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system. The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease. The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications. With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare. - Discusses fundamental and advanced approaches as well as optimization techniques used in AI for healthcare systems - Includes chapters on various established imaging methods as well as emerging methods for skin cancer, brain tumor, epileptic seizures, and kidney diseases - Adopts a bottom-up approach and proposes recent trends in simple manner with the help of real-world examples - Synthesizes the existing international evidence and expert opinions on implementing decommissioning in healthcare - Promotes research in the field of health and hospital management in order to improve the efficiency of healthcare delivery systems