Deploying RL-based ventilation control systems in real-world clinical settings poses several challenges and limitations that need to be addressed for successful implementation. One major challenge is the need for robust validation and testing of the RL algorithms on diverse patient populations to ensure generalizability and safety. This requires extensive clinical trials and validation studies to assess the performance of the RL agents in real clinical scenarios. Additionally, ensuring the interpretability and transparency of the RL policies is crucial for gaining acceptance from healthcare providers and regulatory bodies. Explainable AI techniques can be employed to provide clinicians with insights into the decision-making process of the RL agents. Furthermore, addressing data quality issues, such as missing or noisy data, and ensuring the security and privacy of patient information are essential considerations in deploying RL-based systems in healthcare settings. Collaborating closely with clinicians and healthcare professionals throughout the development and deployment process can help identify and mitigate these challenges effectively.