Article

iMDPath: Interpretable Multi-task Digital Pathology Model for Clinical Pathological Image Prediction and Interpretation

2025-04-17

Abstract excerpt

Deep learning (DL)-based pathological image modelling and analysis approaches offer transformative potential for early cancer diagnostics, yet limited sample sizes and a lack of interpretability often hinder efficient clinical translation. Here, we present the interpretable Multi-Task Digital Pathology Model (iMDPath), an end-to-end highly explainable multi-task deep learning framework that simultaneously addresse...

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Literature Corpus work: 1efeab68-ffc1-5739-be8b-97b07a140467
DOI: 10.1101/2025.04.13.25323912

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