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Found 7 papers, 1 papers with code
FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR
In the past decade, with the development of big data technology, an increasing amount of patient information has been stored as electronic health records (EHRs).
eTREE: Learning Tree-structured Embeddings
In many applications, the categories of items exhibit a hierarchical tree structure.
Representation Learning of EHR Data via Graph-Based Medical Entity Embedding
Automatic representation learning of key entities in electronic health record (EHR) data is a critical step for healthcare informatics that turns heterogeneous medical records into structured and actionable information.
Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks
Rare diseases affecting 350 million individuals are commonly associated with delay in diagnosis or misdiagnosis.
Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model
Many computational models were proposed to extract temporal patterns from clinical time series for each patient and among patient group for predictive healthcare.
Modeling Treatment Delays for Patients using Feature Label Pairs in a Time Series
Pharmaceutical targeting is one of key inputs for making sales and marketing strategy planning.
Semi-supervised Rare Disease Detection Using Generative Adversarial Network
Rare diseases affect a relatively small number of people, which limits investment in research for treatments and cures.
