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 21 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.

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 21 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.

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 21 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.