Mastering Secure Data Anonymization And Pseudonymization A Comprehensive Framework For Privacy And Compliance In The Digital Age

Mastering Secure Data Anonymization and Pseudonymization: A Comprehensive Framework for Privacy and Compliance in the Digital Age

This book delves into the innovative framework for data anonymization and pseudonymization designed to safeguard Personally Identifiable Information (PII) in an era of heightened data privacy concerns and regulatory requirements. With the rapid growth of digital data and stringent regulations like GDPR and HIPAA, organizations face an urgent need to protect sensitive information without sacrificing its utility. Drawing from a patent-pending framework, this book offers a deep exploration into the methodologies, technologies, and applications of secure data handling practices. It provides readers with a step-by-step understanding of the framework's components, including machine learning-based PII detection, advanced anonymization techniques, and controlled re-identification processes. Through real-world examples, practical applications, and insights into regulatory compliance, this book equips professionals, researchers, and policymakers with the knowledge and tools needed to navigate the complexities of data privacy. Readers will gain a comprehensive understanding of how to implement secure data anonymization and pseudonymization, ensuring both privacy and operational efficiency, and learn how to integrate these practices seamlessly into existing data management workflows.

Artificial Intelligence in Medical Imaging

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 implicationsfor 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.

Registries for Evaluating Patient Outcomes