1 citations · 1 across the 2 of their papers we have counts for
2 papers
eess.IV2026
AI End-to-End Radiation Treatment Planning Under One Second
Simon Arberet, Riqiang Gao, Martin Kraus +9
Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving efficiency and consistency in clini…
cs.HC2025★ 1 cited
Automating RT Planning at Scale: High Quality Data For AI Training
Riqiang Gao, Mamadou Diallo, Han Liu +10
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial intelligence (AI) promise to improve its precision and efficiency, but progress is o…