The Future of Artificial Intelligence in X-ray Radiography: Enhancing Healthcare and Workflow Efficiency

Abstract

Artificial intelligence (AI) has revolutionized the medical field, particularly in radiology, by enhancing diagnostic accuracy, improving workflow efficiency, and contributing to improved patient outcomes. This review discusses the role of AI in radiology imaging, focusing on its capabilities in image analysis, disease detection, and task automation. AI techniques, such as machine learning and deep learning, have greatly improved diagnostic processes by recognizing complex patterns in medical images. However, challenges such as data privacy, interpretability of AI algorithms, and integration into existing healthcare systems must be addressed. The future of AI in radiology includes developing robust and interpretable models, ensuring regulatory and ethical compliance, and enhancing collaboration between radiologists and AI experts. Furthermore, the integration of AI with electronic health records and hybrid imaging modalities promises to further enhance the accuracy and efficiency of radiology diagnostics. As AI continues to evolve, it holds great potential to transform radiology and healthcare practices, improve patient care, and shape personalized medicine.