Improving discriminative ability in mammographic microcalcification classification using deep learning: a novel double transfer learning approach validated with an explainable artificial intelligence technique

2025-08-11 radiology and imaging Title + abstract only

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BackgroundBreast microcalcification diagnostics are challenging due to their subtle presentation, overlapping with benign findings, and high inter-reader variability, often leading to unnecessary biopsies. While deep learning (DL) models - particularly deep convolutional neural networks (DCNNs) - have shown potential to improve diagnostic accuracy, their clinical application remains limited by the need for large annotated datasets and the "black box" nature of their decision-making. PurposeTo d...

Improving discriminative ability in mammographic microcalcification classification using deep learning: a novel double transfer learning approach validated with an explainable artificial intelligence technique

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