Full Description
This book offers an in-depth exploration of how innovative technologies are reshaping the landscape of cancer diagnosis, treatment, and care by examining the intersection of precision medicine, digital health, and disruptive scientific advances in oncology and focusing on the integration of molecular profiling, artificial intelligence, and digital health infrastructures to revolutionize cancer care. Through 15 detailed chapters, the book covers a range of cutting-edge topics, including the application of AI and deep learning in oncologic imaging, the rise of liquid biopsy techniques for non-invasive cancer detection, and the powerful synergy of radiogenomics in personalizing patient treatment. It delves into how multi-omics integration and systems biology are being leveraged to understand tumor biology better, predict disease progression, and identify novel therapeutic targets. The book also addresses the evolving role of AI in predictive modeling and decision support systems, providing clinicians with advanced tools for risk stratification and prognostic analysis. It explores the ethical and regulatory challenges of integrating digital technologies into clinical practice and offers a global perspective on the barriers to equitable access in cancer care. Designed for oncologists, researchers, data scientists, biomedical engineers, and healthcare professionals, Precision Digital Oncology bridges the gap between cutting-edge research and real-world application, providing a comprehensive, forward-looking roadmap for the future of cancer treatment. Whether you're exploring the impact of AI in cancer care or seeking insights into the future of digital health technologies, this book offers critical knowledge for anyone interested in the next generation of cancer research and therapeutic strategies.
Contents
Part (I) Conceptual and Scientific Foundations Chapter 1: The Paradigm Shift Toward Precision and Digital Oncology Chapter 2: Molecular Oncology and the Role of Tumor Genomics in Clinical Decision-Making Chapter 3: Systems Biology and Multi-Omics Integration in Cancer Research Chapter 4: The Architecture of Digital Oncology: Data Infrastructures and Health Informatics Chapter 5: Clinical Bioinformatics and Decision Support in Personalized Oncology Part (II) Disruptive Technologies in Diagnostics and Therapeutics Chapter 6: Artificial Intelligence and Deep Learning in Oncologic Imaging and Histopathology Chapter 7: Liquid Biopsies and the Non-Invasive Molecular Profiling of Cancer Chapter 8: Radiogenomics and the Integration of Imaging and Genomic Data Chapter 9: Advanced Therapeutics in Digital Precision Oncology: From Immunotherapies to Cell-Based Treatments Chapter 10: Predictive Modeling and AI-Driven Prognostic Tools in Cancer Management Part (III) Translational Insights, Implementation, and Future Perspectives Chapter 11: Real-World Evidence and Clinical Trial Innovation in the Digital Era Chapter 12: Ethics, Privacy, and Regulatory Challenges in Digital Oncology Chapter 13: Health Equity, Global Access, and the Digital Divide in Oncology Chapter 14: Emerging Technologies: Nanomedicine, Biosensors, and Quantum Tools in Oncology Chapter 15: Strategic Roadmap for Future Oncology: Integrating Innovation into Clinical and Policy Frameworks 16. Application of Artificial Intelligence in Modern Oncology: Trends, Challenges, and Future Directions 17. Clinical Bioinformatics and Decision Support in Personalized Oncology 18. Federated Artificial Intelligence in Drug Discovery and Genomic Research 19. AI-Driven Cancer Detection Using Ensemble Deep Learning on Mammographic and Histopathological Images 20. Blockchain Integration for Trust and Security in Federated Learning 21. Frontiers of Cancer Therapy: Emerging Nanomedicines Revolutionizing Oncology
