This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN. This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine. Provides the history and overview of the various modalities of AI and their applications within each field of medicine Discusses current AI-based medical research, including landmark trials within each field of medicine Addresses the current knowledge gaps that clinicians commonly face that prevent the application of AI-based research to clinical practice Encompasses examples of specific cases and discusses challenges and biases associated with AI

This collection aims to explore the transformative potential of computer vision and artificial intelligence (AI) in revolutionizing medical imaging. Medical imaging is still in a state of infancy. The interpretation of medical images is often time-consuming and subject to human error. By leveraging computer vision algorithms and AI technologies, medical imaging can be enhanced with automated analysis, pattern recognition, and predictive modelling, leading to improved accuracy, speed, and clinical outcomes. This collection provides an overview of the current state, challenges, and prospects of integrating computer vision and AI techniques into existing medical imaging technologies. Medical imaging has the potential to create a paradigm shift in healthcare in future enhancing diagnostic accuracy, personalised treatment, and overall patient care. While challenges related to data quality, interpretability, and ethics must be navigated, the future for AI based imaging technology is bright.

Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field. Artificial Intelligence for Medicine is beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field. - Covers the basic concepts of Artificial Intelligence and Machine Learning, methods and practices, and advanced topics and applications to clinical and precision medicine - Presents readers with an understanding of how AI is revolutionizing medicine by demonstrating the applications of computational intelligence to the field, along with an awareness of how AI can improve upon traditional medical structures - Provides researchers, practitioners, and project stakeholders with a complete guide for applying AI techniques in their projects and solutions

Topic Editor H. Peter Soyer is a shareholder of MoleMap NZ Limited and e-derm consult GmbH, and undertakes regular teledermatological reporting for both companies. He is a Medical Consultant for Canfield Scientific Inc., MetaOptima and Revenio Research Oy and also a Medical Advisor for First Derm.

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.

The Role of Artificial Intelligence in Healthcare the transformative impact of AI technologies on medical practices, research, and patient care. This into AI-driven innovations such as predictive analytics, diagnostic tools, personalized medicine, and robotic surgery, highlighting their potential to improve healthcare outcomes. It addresses ethical considerations, data privacy, and challenges in implementation while showcasing real-world applications and future trends. Designed for healthcare professionals, technologists, and policymakers, the book offers insights into how AI is reshaping the healthcare landscape, making it more efficient, accurate, and accessible.

Implementation of artificial intelligence (AI) in radiology is an important topic of discussion. Advances in AI—which encompass machine learning, artificial neural networks, and deep learning—are increasingly being applied to diagnostic imaging. While some posit radiologists are irreplaceable, certain AI proponents have proposed to "stop training radiologists now." By compiling perspectives from experts from various backgrounds, this book explores the current state of AI efforts in radiology along with the clinical, financial, technological, and societal perspectives on the role and expected impact of AI in radiology.