Improving Diagnostic Accuracy with AI-Enhanced Imaging Techniques
Abstract
Diagnostic imaging is a critical component of modern healthcare, and artificial intelligence (AI) is significantly enhancing its accuracy and efficiency. This paper reviews the latest advancements in AI-powered imaging techniques, including deep learning models for image recognition and analysis. The study showcases how AI can assist radiologists in detecting abnormalities, reducing diagnostic errors, and streamlining workflow. Case studies of AI applications in detecting cancers, cardiovascular diseases, and neurological disorders are presented. The paper also addresses the challenges of implementing AI in diagnostic imaging, such as the need for large annotated datasets, regulatory hurdles, and the importance of maintaining human oversight.
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