Deep Reinforcement Learning in Healthcare and Bio-Medical Applications

Deep reinforcement learning (DRL), which learns a set of behaviors that maximize the projected reward, combines the representational power of deep neural networks with the reinforcement learning paradigm. DRL holds great promise for the future of healthcare and medicine, according to recent studies.An overview of the research on DRL in medical imaging is provided in this article. We start with a comprehensive DRL course that covers both the most recent model-based and model-free approaches. The tasks covered in the next section of this article are loosely divided into three main categories: (i) parametric medical image analysis tasks like landmark detection,object/lesion detection, registration, and view plane localization; optimization tasks like hyperparameter tuning, augmentation strategy selection, and neural architecture search; and (iii) other applications like surgical gesture segmentation, person tracking, and perso The study finishes with thoughts of potential future directions.