INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE INTERPRETATION OF MEDICAL IMAGING: BENEFITS, LIMITATIONS, AND CHALLENGES
DOI:
https://doi.org/10.63330/aurumpub.061-025Keywords:
Artificial Intelligence, Radiology, Diagnostic Imaging, Deep Learning, Patient Safety, Medical RegulationAbstract
Artificial intelligence (AI)—particularly through machine learning algorithms and deep neural networks—represents a transformation in radiology and diagnostic imaging. Its integration aims to enhance accuracy, standardize analysis, streamline workflows, and reduce errors associated with fatigue or inter-observer variability. This article reviews technical principles, proven clinical applications, and operational and diagnostic benefits, while also addressing methodological limitations, ethical risks, regulatory issues, and challenges regarding its safe and responsible implementation within the Brazilian healthcare system. It concludes that AI serves as an assistive tool rather than a substitute for medical professionals, requiring rigorous governance and continuous validation.
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References
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