Hybrid artificial intelligence (AI) and Monte Carlo (MC) methods for radiotherapy dose calculation refer to computational approaches that integrate machine learning models with physics-based MC simulation to achieve both fast and accurate estimation of radiation dose distributions. These methods use AI to approximate complex MC dose calculations with greatly reduced computation time, while retaining MC simulation as the standard for physical fidelity and validation. The hybrid strategy supports real-time or near-real-time dose evaluation, enables adaptive treatment workflows, and allows accurate modeling of photon and electron beams in heterogeneous patient anatomy. By combining the strengths of data-driven prediction and physics-based simulation, hybrid AI and MC methods provide a pathway toward efficient and high-precision dose calculation in modern radiotherapy.
W. K. Chow (Fri,) studied this question.