Abstract
The assimilation of Artificial Intelligence (AI) into radiology marks a significant milestone in medical diagnostic procedures. This article examines the varied effects of AI developments in radiology, considering both the advantageous prospects and the possible challenges. AI's application in radiology, primarily through machine learning and deep learning techniques, offers unprecedented improvements in diagnostic accuracy, efficiency, and patient care. However, these advancements also bring forth significant challenges, including ethical dilemmas, potential job displacement, and data security concerns. Through a balanced examination of current literature and case studies, this editorial aims to provide a comprehensive understanding of AI's role in reshaping radiology. It discusses how AI can revolutionize diagnostic practices while addressing the critical issues accompanying its implementation. The goal is to present a nuanced perspective, acknowledging AI's potential to enhance radiology, alongside the importance of addressing the complexities of this technological evolution.
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