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Liver lesions are abnormal areas in the liver that may be harmless or a sign of serious diseases like cancer. Detecting and correctly identifying these lesions is important for early treatment. Traditionally, doctors analyze medical images like CT or MRI scans to find and classify these lesions. However, this process can be time-consuming and may vary between doctors. In this project, we use machine learning – a type of artificial intelligence – to help automatically analyze medical images and classify liver lesions. By training the system on a large number of labeled images, the computer learns to recognize patterns and make predictions about new, unseen images. This approach can support doctors by providing fast, consistent, and accurate results. Our study shows that machine learning can be a powerful tool in medical imaging and may help improve the early diagnosis and treatment of liver-related diseases.