AI Research
An Asynchronous Federated Learning Platform for Lung Adenocarcinoma Grading via Foundation Models and Structural Pruning
A proposed platform targets lung adenocarcinoma grading amid pathologist disagreement.
Classification of lung adenocarcinoma into poorly differentiated (PD) and well-to-moderately differentiated (WMD) subtypes plays an important role in patient survival; however, consistent classification is difficult due to inter-observer variability among pathologists.
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ArXiv CS.LG
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ArXiv CS.LG
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Consistent grading of lung adenocarcinoma matters because the distinction between poorly differentiated and well-to-moderately differentiated subtypes plays a role in patient survival. The proposed platform applies federated learning and foundation models to this task, which is challenging because pathologists may disagree.
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