The rapid advancement in Artificial Intelligence (AI) has significantly transformed the field of radiotherapy, offering opportunities to enhance precision, efficiency, and patient outcome. AI-driven technologies, including machine learning (ML) and deep learning (DL) algorithms, have been integrated into various stages of radiotherapy, such as imaging and treatment planning. One major trend in application is the use of AI for automated contouring of organs and tumors, thus reducing the time-intensive and operator-dependent nature of manual processes.
Such technologies have been implemented at different phases in HA oncology centers. Despite the opportunities offered by AI, several challenges and pitfalls remain. Bias and quality issues in training datasets can hinder the reliability of AI models. The "black-box" nature of many AI algorithms poses barriers to clinical adoption, as healthcare providers demand interpretability and transparency. AI applications may also create hard-to-detect errors in specific clinical scenarios. Healthcare professionals should therefore be well educated in the subject, and critically evaluate the AI algorithms to be adopted. Creating a sustainable and efficient workflow for the entire treatment process should be the ultimate goal, and AI is an invaluable tool in the task. Besides technologies available on the market, local research institutes are active to incorporate AI into healthcare. Close collaboration with researchers can keep our healthcare professionals abreast on technology frontiers, and also to devise suitable AI solutions in solving clinical problems.
In conclusion, AI presents a transformative opportunity in radiotherapy. Collaborative efforts involving clinicians, allied health professionals and researchers are essential to maximize the benefit of AI.
