Deep learning (DL) is transforming oncology by leveraging convolutional neural networks (CNNs), graph neural networks (GNNs), and Vision Transformers to analyze complex medical imaging and genomic data, with diagnostic accuracies in specific cancers often exceeding 95%. While promising, clinical integration faces hurdles regarding the "black box" nature of AI, data heterogeneity, and lower sensitivity in detecting early-stage cancers. For a comprehensive overview of AI in clinical cancer detection, read this study from ScienceDirect .

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