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Semi-Supervised Graph Representation Learning with Human-centric Explanation for Predicting Fatty Liver Disease
Addressing the challenge of limited labeled data in clinical settings, particularly in the prediction of fatty liver disease, this study explores the potential of graph representation learning within a semi-supervised learning framework.
Electrochemically stable lithium-ion and electron insulators (LEIs) for solid-state batteries
Rechargeable solid-state Li metal batteries demand ordered flows of Li-ions and electrons in and out of solid structures, with repeated waxing and waning of LiBCC phase near contact interfaces which gives rise to various electro-chemo-mechanical challenges.
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