Embracing Artificial Intelligence in Radiology: Balancing Its Potential Benefits with Current Limitations in Clinical Practice

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The workload of radiologists has increased significantly, prompting interest in artificial intelligence (AI) as a potential aid in diagnostic processes.
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Deep learning, a machine learning strategy, has shown promise in radiology by identifying patterns in large datasets, enhancing diagnostic accuracy.
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AI models can outperform average radiologists in detecting certain findings, but they may also overlook rare but critical conditions.
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Despite the benefits of AI, it cannot replace radiologists or their education, as it may miss vital findings and relies on clinical context.
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The integration of AI tools in clinical practice is feasible, but challenges like reimbursement issues and the need for user education remain.

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