This conference is intended to enhance the overall fund of knowledge required for the radiation oncologist to treat patients in all oncologic subspecialties and to inform the radiation oncologist on quality delivery of these technologies.
Key Words: Radiation Oncology, Research, Oncology
- Physicians
- Nurse Practitioners
- Physician Assistants
- Physics, Physics Residents, Medical Residents
Participants who engage in this educational intervention will be able to:
- Describe emerging artificial intelligence (AI)-driven methods and their applications within modern radiotherapy workflows.
- Explain the role of large language models (LLMs) in supporting clinical and operational radiotherapy workflows.
- Evaluate the potential applications of LLMs and other AI technologies in treatment plan optimization and adaptive radiotherapy.
- Discuss the clinical implications of AI-enabled radiotherapy approaches for the management of cancer patients.
- William Hall, MD
- Ergun Ahunbay, PhD
Contact
ACCME Accreditation Statement:
The Medical College of Wisconsin is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
AMA Credit Designation Statement:
The Medical College of Wisconsin designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Hours of Participation for Allied Health Care Professionals:
The Medical College of Wisconsin designates this activity for up to 1.00 hours of participation for continuing education for allied health professionals.
- 1.00 AMA PRA Category 1 Credit(s)™AMA PRA Category 1 Credit(s)™
- 1.00 Hours of ParticipationHours of Participation credit.

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