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Found 4 papers, 1 papers with code
Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC)
As a solution, we propose an end-to-end learning of imputation and disease prediction of incomplete medical datasets via Multigraph Geometric Matrix Completion (MGMC).
Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time
Computer-aided diagnosis (CADx) algorithms in medicine provide patient-specific decision support for physicians.
Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets
Recently, several works proposed geometric deep learning approaches to solve disease classification, by modeling patients as nodes in a graph, along with graph signal processing of multi-modal features.
Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion
In this work, we follow up on the idea of modeling multi-modal disease classification as a matrix completion problem, with simultaneous classification and non-linear imputation of features.
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