The article “Role of Artificial Intelligence in Reducing Error Rates in Radiology: A Scoping Review” explores the significant impact of AI technologies in enhancing diagnostic accuracy and efficiency in radiology. It highlights how AI algorithms, particularly machine learning and deep learning, assist radiologists by identifying abnormalities in imaging data, thus minimizing human error. The scoping review outlines various studies demonstrating AI’s ability to improve error detection rates in x-rays, CT scans, and MRIs. Additionally, it discusses the integration of AI tools in clinical workflows, emphasizing the importance of collaboration between radiologists and AI systems. The review also addresses potential challenges, including data privacy concerns and the need for ongoing training of AI models. Overall, the findings support the adoption of AI in radiology, suggesting that these technologies can significantly reduce error rates, ultimately leading to better patient outcomes and enhanced healthcare quality.
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The Impact of Artificial Intelligence on Minimizing Error Rates in Radiology: A Comprehensive Scoping Review – Cureus

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