Article

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

Abstract excerpt

<h4>Background: </h4> Breast 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...

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Literature Corpus work: b32d4c3e-0277-522a-abc1-80d0dd439ca1
DOI: 10.1101/2025.08.05.25332967

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