A machine learning approach has been applied to the prediction of magnetic hysteresis properties (coercive field, remanence, and loop area) nanoparticles for hyperthermia applications. Trained on a dataset compiled from numerical simulations, neural network random forest were used predict power losses as function their intrinsic (saturation, anisotropy, size) mutual interactions, well applicati...