Artificial Intelligence in Radiation Oncology and Biomedical Physics 1st Edition

Capture the future of cancer care with Artificial Intelligence in Radiation Oncology and Biomedical Physics, 1st Edition — a definitive guide that bridges cutting-edge AI techniques and practical clinical application for radiation oncology and medical physics professionals.

This authoritative volume dives into machine learning, deep learning, and data-driven modeling tailored to radiotherapy workflows: image segmentation, adaptive treatment planning, outcome prediction, quality assurance, and workflow automation. Clear explanations and real-world case studies make complex algorithms accessible to clinicians, medical physicists, dosimetrists, biomedical engineers, and AI researchers seeking to translate innovation into safer, more efficient patient care.

What sets this book apart is its balance of theory and practice. Readers will find critical discussions on model validation, interpretability, regulatory considerations, and ethical use of patient data — essential for adoption across hospitals, cancer centers, and academic institutions worldwide. Practical examples and implementation strategies help teams accelerate integration of AI tools into clinical routines while maintaining rigorous safety standards.

Whether you’re updating a departmental library, preparing for research collaboration, or enhancing clinical decision-making, this 1st edition furnishes the knowledge needed to lead AI-driven transformation in radiation oncology. Packed with actionable insights and global perspectives, it’s an indispensable resource for anyone committed to improving radiotherapy outcomes through technology.

Add Artificial Intelligence in Radiation Oncology and Biomedical Physics, 1st Edition to your collection today and equip your practice or research with the expertise to navigate the next generation of precision cancer care.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.