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https://pubmed.ncbi.nlm.nih.gov/38091333
A deep neural network trained on a large-scale, heterogeneous dataset of 4.5 million medical images achieves significant modality classification accuracy, demonstrating the potential of using deep learning models for efficiently handling hyper-scale multimodal imaging datasets in real-world applications.