Precision Digital Oncology
CRC Press (Verlag)
9781041153597 (ISBN)
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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.
Wasswa Shafik is an IEEE member and Team Lead at the Dig Connectivity Research Laboratory (DCRLab) in Kampala, Uganda. He holds a PhD in Digital Science (Computer Science) from the School of Digital Science, Universiti Brunei Darussalam. Wasswa also earned a Master’s degree in Information Technology Engineering from Yazd University, Iran, and a Bachelor’s degree in Information Technology from Ndejje University, Uganda. Wasswa has received specialized training from the National Institutes of Health (NIH), the U.S. Department of Health and Human Services, and the Bloomberg School of Public Health, focusing on Data Quality, Monitoring and Evaluation Fundamentals, and Protecting Human Research Participants. Before his PhD, he worked as a Community Data Officer at Pace-Uganda, a Research Associate at TechnoServe and Mercy Corps, a Research Assistant at PSI-Uganda, a Research Lead at the Socio-economic Data Centre (SEDC-Uganda), and a former Agricultural Managing Director at Asmaah Charity Organisation. His research focuses on developing computationally efficient models for challenges in health, agriculture, and ecology. He specializes in Artificial Intelligence, Computer Vision, Neural Networks, and the Internet of Things, with applications in Smart Agriculture, Digital Health, and Ecological Informatics. Dr. Jay Kumar Pandey is currently working as an Assistant Professor in the Department of Electrical & Electronics Engineering at Shri Ramswaroop Memorial University, Barabanki (U.P.) India. Dr. Pandey has completed his Ph.D. and has done his M.Tech. with specialization in Power Control (Instrumentation) and also done his MBA from Finance and Marketing. His subjects of interest are related to Artificial Intelligence ,Biomedical & Healthcare, Image Processing, Machine Learning and Renewable energy. He has 15 years of teaching and research experience has published more than 30 research papers in National and International journals /conferences & Book Chapters in CRC, NOVA, Taylor & Francis, Springer and IGI Publisher. Dr. Pandey is an editor of books (edited) published by reputed publishers Apple Academy Press, IGI, Elsevier, Wiley-IEEE, NOVA, Bentham Science ,IAP, Emerald Publication ,Taylor & Francis & Cambridge Scholar. Dr. Pandey is also Editor of Journal of Technology Innovations and Energy United States. Dr. Pandey having reviewer in different conference/Journal/Book Chapters like (The Journal of Supercomputing in Springer Nature, IGI publishing, Journal of Security and Communication Networks Hindawi, Journal of Biomimetics, Biomaterials and Biomedical Engineering (JBBBE) Scientific Net, Switzerland, Advanced Engineering Forum (AEF) Scientific Net, Switzerland) Haipeng Liu received his Bachelor and Master in Engineering degrees from Zhejiang University, China, in 2012 and 2015, respectively, and Doctor of Philosophy in Medical Sciences from the Chinese University of Hong Kong, in 2018. From 2019 to 2020, he was a research fellow with the Medical Technology Research Center, Anglia Ruskin University. Since 2020, he has been a research fellow with Coventry University, UK. He is the author of over 60 journal articles and 10 conference papers. He has delivered 12 invited talks for international conferences, universities, and research institutes. He is a receiver of two British Heart Foundation Travel Awards, a Director of Studies (Dos) of two PhD students, and an editorial member of six academic journals. He is a reviewer of more than 60 articles from 24 journals, 4 international conferences, and one book proposal. His research interests include biomechanics, physiological measurement, and computational simulation of cardiovascular diseases.
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
| Erscheint lt. Verlag | 6.7.2026 |
|---|---|
| Zusatzinfo | 23 Tables, black and white; 8 Line drawings, color; 2 Line drawings, black and white; 2 Halftones, color; 10 Illustrations, color; 2 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 210 x 280 mm |
| Themenwelt | Medizin / Pharmazie ► Medizinische Fachgebiete ► Onkologie |
| Studium ► Querschnittsbereiche ► Prävention / Gesundheitsförderung | |
| Naturwissenschaften ► Biologie ► Zellbiologie | |
| ISBN-13 | 9781041153597 / 9781041153597 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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