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Found 3 papers, 2 papers with code
DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency
The combination of electronic health records (EHR) and medical images is crucial for clinicians in making diagnoses and forecasting prognosis.
Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records
Such methods generally require an input tensor describing the inter-modal interactions to be pre-established; however, the correspondence between different modalities (e. g., correspondence between medications and diagnoses) can often be missing in practice.
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
In particular, we define the N-th order tensor Wasserstein loss for the widely used tensor CP factorization and derive the optimization algorithm that minimizes it.
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