Artificial intelligence in nuclear cardiology: Enhancing diagnostic accuracy and efficiency

Artificial intelligence (AI) is rapidly reshaping cardiovascular imaging, with nuclear cardiology uniquely positioned to benefit. By addressing the technical complexity of image acquisition, reconstruction, and interpretation, AI can enhance image quality, reduce radiation exposure, and improve efficiency. Beyond image optimization, AI enables virtual attenuation correction and automated quantification of novel risk markers that are otherwise impractical to assess manually. Machine learning models can also integrate multimodal data, including clinical, stress, and imaging features, to support more accurate diagnosis and to refine risk stratification. Deep learning can be used to provide direct diagnostic or risk stratification estimates from nuclear cardiology images. This review highlights recent advances in AI within nuclear cardiology, outlines their potential to transform clinical workflows, and discusses future directions for integrating these tools into routine practice.