CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks
Electronic Health Records (EHRs) play a crucial role in shaping predictive are models, yet they encounter challenges such as significant data gaps and class imbalances. Traditional Graph Neural Network (GNN) approaches have limitations in fully leveraging neighbourhood data or demanding intensive co...
Main Authors: | Molaei, S, Bousejin, NG, Ghosheh, GO, Thakur, A, Chauhan, VK, Zhu, T, Clifton, DA |
---|---|
Formato: | Journal article |
Idioma: | English |
Publicado: |
Springer
2024
|
Títulos similares
-
Learning graph representations with maximal cliques
por: Molaei, S, et al.
Publicado: (2021) -
Incarnation in Ludics and maximal cliques of paths
por: Myriam Quatrini, et al.
Publicado: (2013-10-01) -
Broadcasting in Stars of Cliques and Path-Connected Cliques
por: Akash Ambashankar, et al.
Publicado: (2025-02-01) -
Towards Optimal Output-Sensitive Clique Listing or: Listing Cliques from Smaller Cliques
por: Dalirrooyfard, Mina, et al.
Publicado: (2024) -
Cliques and Clique Covers in Interval-Valued Fuzzy Graphs
por: Napur Patra, et al.
Publicado: (2021-06-01)