Artificial intelligence in radiology

Abstract

Artificial intelligence (AI) is revolutionizing clinical medicine, particularly radiology, by enhancing diagnostic accuracy and streamlining operational efficiency. Radiology benefits from AI’s prowess in image pattern recognition, which not only augments radiologists’ capabilities but also optimizes tasks such as scheduling and radiation monitoring. AI’s applications span diagnostic and interventional radiology, enabling the interpretation of complex imaging data through advanced technologies such as convolutional neural networks and radiomics. These tools help detect subtle disease indicators often missed by the human eye. AI also improves radiology department management by automating routine tasks and prioritizing urgent cases to ensure timely medical interventions. Educational programs must evolve to prepare the next generation of radiologists for a future where AI is ubiquitous in their professional landscape. However, integrating AI into radiology brings challenges, including ethical and legal concerns about patient privacy, data security, and potential bias in algorithms. Ethical and legal concerns must be addressed by developing robust guidelines that keep pace with technological advancements. Addressing these issues requires rigorous validation of AI tools across various clinical settings and demographics. Undoubtedly, AI will empower radiologists, enhance their diagnostic capabilities and accuracy, and contribute to precision and personalized medicine.