Artificial intelligence in medical physics

Abstract Artificial intelligence (AI) has profoundly transformed medical physics across its entire spectrum. Starting from data acquisition, AI has introduced innovations in the processing of imaging data, including denoising and image enhancement. It plays a key role in diagnosis by maximizing the informational content of medical data and supporting clinical decision-making, enhancing both interpretability and transparency through the emerging field of Explainable AI. AI has made significant contributions in areas such as radiotherapy planning optimization, real-time monitoring, and dosimetry, thereby accelerating simulations, reducing errors, and enhancing treatment precision. In the field of interventions, AI is guiding robotic-assisted surgery and intraoperative procedures, enhancing both accuracy and safety. Moreover, AI is streamlining hospital workflows, automating reporting, and enabling operational intelligence. Collectively, these advancements are improving efficiency, accuracy, and patient outcomes, while safeguarding the indispensable role of human care in medicine. This review tries to explore the key advancements enabled by AI in medical physics following the pathway from data acquisition to diagnosis, therapy, and intervention. Looking ahead, personalized care, enabled by digital twins, will make treatments more precise and less invasive. At the same time, generative AI will support healthcare professionals by automating routine tasks, allowing them to focus more on patient relationships and the human side of care.