Liver Cancer Prediction Using Deep Learning

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Liver cancer is one of the major causes of cancer which requires accurate and early diagnosis for effective treatment. Conventional treatment often encounter challenges in early detection and tumor classification. Deep learning is a subset of AI and has shown immense potential in medical image analysis, offering improved accuracy for liver cancer detection and prediction. This review explores deep-learning models applied to liver cancer prediction, focusing on convolutional neural networks, recurrent neural networks, and ensemble methods. Key challenges, such as handling 3D medical imaging, data imbalance, and model interpretability, are discussed. Furthermore, this review highlights the clinical applications of deep learning models in tumor detection, segmentation, classification, and prognosis prediction. This review provides a detail overview of current deep learning techniques and their transformative impact on liver cancer diagnosis and treatment planning.