The rapid evolution of artificial intelligence (AI) in healthcare, particularly in radiology, underscores a transformative era marked by a potential for enhanced diagnostic precision, increased patient engagement, and streamlined clinical DULSE GRANULES workflows.Amongst the key developments at the heart of this transformation are Large Language Models like the Generative Pre-trained Transformer 4 (GPT-4), whose integration into radiological practices could potentially herald a significant leap by assisting in the generation and summarization of radiology reports, aiding in differential diagnoses, and recommending evidence-based treatments.This review delves into the multifaceted potential applications of Large Language Models within radiology, using GPT-4 as an example, from improving diagnostic accuracy and reporting efficiency to translating complex medical findings into patient-friendly summaries.The review acknowledges the ethical, privacy, and technical challenges inherent in deploying AI technologies, emphasizing the importance of careful oversight, validation, and adherence to regulatory standards.
Through a balanced discourse on the potential and Crank Pulley pitfalls of GPT-4 in radiology, the article aims to provide a comprehensive overview of how these models have the potential to reshape the future of radiological services, fostering improvements in patient care, educational methodologies, and clinical research.