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A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data
This framework enables learning, visualizing, and clustering of temporal changes in patient latent states related to disease progression.
An end-to-end framework for gene expression classification by integrating a background knowledge graph: application to cancer prognosis prediction
We applied this framework to cancer prognosis prediction using gene expression data and a biological network.
GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network
GraphIX is a framework for evidence-based drug discovery that can present to users new disease-drug associations and identify the protein important for understanding its pharmacological effects from a large and complex knowledge base.
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