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This research investigates the diagnostic accuracy of delayed phase post-contrast computed tomographic (CT) images for identifying focal liver lesions (FLLs) in dogs, analyzing 69 cases. The study identifies significant qualitative and quantitative CT features that can differentiate between four categories of FLLs: hepatocellular carcinoma, nodular hyperplasia, other benign lesions, and other malignant lesions. A machine learning-based decision tree was developed, achieving varying accuracy rates for classi

Author

Luciana

Language

EN