The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning | Zendy

Tucker Netherton | Zendy; Carlos Cárdenas | Zendy; Dong Joo Rhee | Zendy; Laurence E. Court | Zendy; Beth M. Beadle | Zendy

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The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning

Author(s) -

Tucker Netherton,

Carlos Cárdenas,

Dong Joo Rhee,

Laurence E. Court,

Beth M. Beadle

Publication year - 2020

Publication title -

oncology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.987

H-Index - 98

eISSN - 1423-0232

pISSN - 0030-2414

DOI - 10.1159/000512172

Subject(s) - radiation oncology , transformative learning , context (archaeology) , deep learning , creativity , medicine , radiation therapy , artificial intelligence , medical physics , oncology , computer science , psychology , paleontology , pedagogy , social psychology , biology

The future of artificial intelligence (AI) heralds unprecedented change for the field of radiation oncology. Commercial vendors and academic institutions have created AI tools for radiation oncology, but such tools have not yet been widely adopted into clinical practice. In addition, numerous discussions have prompted careful thoughts about AI's impact upon the future landscape of radiation oncology: How can we preserve innovation, creativity, and patient safety? When will AI-based tools be widely adopted into the clinic? Will the need for clinical staff be reduced? How will these devices and tools be developed and regulated?

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