AI AND THE FUTURE OF MEDICAL IMAGING A CRITICAL ANALYSIS OF RADIOLOGISTS’ ADAPTATION TO AI-POWERED DIAGNOSTIC SYSTEMS
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Keywords
Artificial Intelligence, Radiology, Medical Imaging, AI Integration, Diagnostic Accuracy, AI-Human Collaboration, AI Training, Healthcare Policy
Abstract
Radiology experiences rapid changes through artificial intelligence, which provides higher diagnostic abilities and increased efficiency and automated capabilities in medical imaging analysis. The study utilized quantitative survey data and face-to-face interviews with radiology experts to accomplish its goals. CT and MRI observations reached 85% and 80% support from medical staff because of precise image interpretation capabilities. However, ultrasound and PET scan acceptance stood at 70% and 65% because of unpredictable real-time imaging conditions. Slow adoption of AI in healthcare results from the combination of three main obstacles, which include AI literacy gaps affecting 63% of professionals while 52% face interoperability issues and regulatory ambiguities affecting 47% of users. Radiologists now see AI as a decision-supporting system rather than a replacement because of their diminishing concern about job loss.
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Muhammad Qadoos
Department of Computer Science, Missouri State University, Springfield, Missouri, USA
Muhammad Haroon
Department of Electrical Engineering, University of Lahore, Islamabad campus, Islamabad, Pakistan
Kohinoor Pirzada
Department of Electrical Engineering, University of Lahore, Islamabad campus, Islamabad, Pakistan