2021
DOI: 10.48550/arxiv.2103.03305
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs

Abstract: Kidney transplantation can significantly enhance living standards for people suffering from end-stage renal disease. A significant factor that affects graft survival time (the time until the transplant fails and the patient requires another transplant) for kidney transplantation is the compatibility of the Human Leukocyte Antigens (HLAs) between the donor and recipient. In this paper, we propose new biologically-relevant feature representations for incorporating HLA information into machine learning-based surv… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 21 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?