ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2022
A Latent Space Model for HLA Compatibility Networks in Kidney Transplantation.
Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 0 citations in OpenAlex.
- LIT-LVM: Structured Regularization for Interaction Terms in Linear Predictors using Latent Variable Models.Transactions on machine learning research · 2025Article
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2 authors at 1 institution in 1 country.
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Abstract
Kidney transplantation is the preferred treatment for people suffering from end-stage renal disease. Successful kidney transplants still fail over time, known as graft failure; however, the time to grant failure, or graft survival time, can vary significantly between different recipients. A significant biological factor affecting graft survival times is the compatibility between the human leukocyte antigens (HLAs) of the donor and recipient. We propose to model HLA compatibility using a network, where the nodes denote different HLAs of the donor and recipient, and edge weights denote compatibilities of the HLAs, which can be positive or negative. The network is
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