Published Paper Details:

The integration of Artificial Intelligence (AI) into medical imaging has transformed diagnostic procedures, enabling enhanced accuracy, efficiency, and predictive capabilities. This study evaluates the current applications of AI in medical imaging, focusing on its role in image analysis, disease detection, and workflow optimization. Key advancements in deep learning algorithms, including convolutional neural networks (CNNs) and generative adversarial networks (GANs), have led to significant improvements in detecting abnormalities, segmenting images, and predicting patient outcomes. Despite its benefits, the adoption of AI in medical imaging presents challenges, including data privacy concerns, interpretability of AI models, and integration into clinical workflows. This paper highlights the potential of AI to revolutionize medical imaging while addressing the ethical and regulatory considerations required to ensure safe and effective implementation. Our findings support AI's ability to complement radiologists and enhance patient care quality, emphasizing the need for continuous innovation and collaboration in this evolving field.