Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep learning models are presented in each chapter to show how they can assist in the efficient processing of breast images. The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine learning classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications. - Presents novel ideas for AI based mammogram data analysis - Discusses the roles deep learning and machine learning techniques play in efficient processing of mammogram images and in the accurate defining of different types of breast cancer - Features dozens of real-world case studies from contributors across the globe

The book uniquely explores the fundamentals of blockchain and digital twin and their uses in smart hospitals. Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals provides fundamental information on blockchain and digital twin technology as effective solutions in smart hospitals. Digital twin technology enables the creation of real-time virtual replicas of hospital assets and patients, enhancing predictive maintenance, operational efficiency, and patient care. Blockchain technology provides a secure and transparent platform for managing and sharing sensitive data, such as medical records and pharmaceutical supply chains. By combining these technologies, smart hospitals can ensure data security, interoperability, and streamlined operations while providing patient-centered care. The book also explores the impact of collected medical data from real-time systems in smart hospitals, and by making it accessible to all doctors via a smartphone or mobile device for fast decisions. Inevitable challenges such as privacy concerns and integration costs must, of course, be addressed. However, the potential benefits in terms of improved healthcare quality, reduced costs, and global health initiatives makes the integration of these technologies a compelling avenue for the future of healthcare. Some of the topics that readers will find in this book include: Wireless Medical Sensor Networks in Smart Hospitals ● DNA Computing in Cryptography ● Enhancing Diabetic Retinopathy and Glaucoma Diagnosis through Efficient Retinal Vessel Segmentation and Disease Classification ● Machine Learning-Enabled Digital Twins for Diagnostic And Therapeutic Purposes ● Blockchain as the Backbone of a Connected Ecosystem of Smart Hospitals ● Blockchain for Edge Association in Digital Twin Empowered 6G Networks ● Blockchain for Security and Privacy in Smart Healthcare ● Blockchain-Enabled Internet of Things (IoTs) Platforms for IoT-Based Healthcare and Biomedical Sector ● Electronic Health Records in a Blockchain ● PSO-Based Hybrid Cardiovascular Disease Prediction for Using Artificial Flora Algorithm ● AI and Transfer Learning Based Framework for Efficient Classification And Detection Of Lyme Disease ● Framework for Gender Detection Using Facial Countenances ● Smartphone-Based Sensors for Biomedical Applications ● Blockchain for Improving Security and Privacy in the Smart Sensor Network ● Sensors and Digital Twin Application in Healthcare Facilities Management ● Integration of Internet of Medical Things (IoMT) with Blockchain Technology to Improve Security and Privacy ● Machine Learning-Driven Digital Twins for Precise Brain Tumor and Breast Cancer Assessment ● Ethical and Technological Convergence: AI and Blockchain in Halal Healthcare ● Digital Twin Application in Healthcare Facilities Management ● Cloud-based Digital Twinning for Structural Health Monitoring Using Deep Learning. Audience The book will be read by hospital and healthcare providers, administrators, policymakers, scientists and engineers in artificial intelligence, information technology, electronics engineering, and related disciplines.

This book uncovers the stakes and possibilities of handling pandemic diseases with the help of Computational Intelligence, using cases and applications from the current Covid-19 pandemic. The book chapters will focus on the application of CI and its related fields in managing different aspects of Covid-19, including modelling of the disease spread, data-driven prediction, identification of disease hotspots, and medical decision support.

Frontiers in Oncology is delighted to present the ‘Reviews in’ series of article collections. Reviews in Breast Cancer will publish high-quality review articles on key topics in the field. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. The Reviews in Breast Cancer collection welcomes full-length, mini or systematic review papers. New articles will be added to this collection as they are published.

This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.

Artificial intelligent systems, which offer great improvement in healthcare sector assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing provide more intelligent and convenient solutions and services. With the help of the advanced techniques, now a days it is possible to understand human body and to handle & process the health data anytime and anywhere. It is a smart healthcare system which includes patient, hospital management, doctors, monitoring, diagnosis, decision making modules, disease prevention to meet the challenges and problems arises in healthcare industry. Furthermore, the advanced healthcare systems need to upgrade with new capabilities to provide human with more intelligent and professional healthcare services to further improve the quality of service and user experience. To explore recent advances and disseminate state-of-the-art techniques related to intelligent healthcare services and applications. This edited book involved in designing systems that will permit the societal acceptance of ambient intelligence including signal processing, imaging, computing, instrumentation, artificial intelligence, internet of health things, data analytics, disease detection, telemedicine, and their applications. As the book includes recent trends in research issues and applications, the contents will be beneficial to Professors, researchers, and engineers. This book will provide support and aid to the researchers involved in designing latest advancements in communication and intelligent systems that will permit the societal acceptance of ambient intelligence. This book presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications healthcare sector and to present the latest snapshot of the ongoing research as well as to shed further light on future directions in this space. The aim of publishing the book is to serve for educators, researchers, and developers working in recent advances and upcoming technologies utilizing computational sciences.

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

Cancer research is currently a vital field of study as it affects a wide range of the population either directly or indirectly. Breast and cervical cancer are two prevalent types that pose a threat to women’s health and wellness. Due to this, further research on the importance of medical informatics within this field is necessary to ensure patients receive the best possible attention and care. The Research Anthology on Medical Informatics in Breast and Cervical Cancer provides current research and information on how medical informatics are utilized within the field of breast and cervical cancer and considers the best practices and challenges of its implementation. Covering key topics such as women’s health, wellness, oncology, and patient care, this major reference work is ideal for medical professionals, nurses, oncologists, policymakers, researchers, academicians, scholars, practitioners, instructors, and students.

"This book provides a comprehensive overview of machine learning research and technology in medical decision-making based on medical images"--Provided by publisher.

Over the decades, the fields of health information systems and informatics have seen rapid growth. Such integrative efforts within the two disciplines have resulted in emerging innovations within the realm of medicine and healthcare. The Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics provides emerging research on the innovative practices of information systems and informatic software in providing efficient, safe, and impactful healthcare systems. While highlighting topics such as conceptual modeling, surveillance data, and decision support systems, this handbook explores the applications and advancements in technological adoption and application of information technology in health institutions. This publication is a vital resource for hospital administrators, healthcare professionals, researchers, and practitioners seeking current research on health information systems in the digital era.