Abstract: Embodiments described herein provide for training an artificial intelligence model to become a preference-aware model. The artificial intelligence model preferences as the artificial intelligence model trains. Reinforcement learning is used to train experts in the artificial intelligence model such that each expert is trained to converge to a unique preference. The architecture of the artificial intelligence model is highly flexible. Upon executing a trained model, users can select automatically images according to various preferences based on medical professional preferences, geographic preferences, patient anatomy, and institutional guidelines.