The rapid advancement of Generative Artificial Intelligence (GenAI) has sparked widespread interest in the field of medical imaging, revealing unprecedented potential in diverse biomedical applications. Recent developments have enabled GenAI systems to perform at a level comparable to experienced clinicians, capable of generating highly accurate and structured medical reports, providing auxiliary diagnostic suggestions, and supporting complex clinical decision-making processes. By automating routine documentation, analyzing imaging data, and integrating multimodal patient information, GenAI can significantly reduce physician workload, minimize diagnostic errors, and improve the efficiency and clarity of doctor-patient communication. Beyond immediate clinical utility, these technologies hold promise for personalized medicine, predictive diagnostics, and large-scale epidemiological studies, offering transformative opportunities to enhance healthcare delivery and optimize clinical workflows. As research continues, the integration of GenAI into standard medical practice may redefine the role of clinicians, promoting more informed, data-driven, and patient-centered care.
Yiran Sun (Sun,) studied this question.