Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Lear...
Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering
About this item
Full title
Author / Creator
Thongprayoon, Charat , Vaitla, Pradeep , Jadlowiec, Caroline C , Leeaphorn, Napat , Mao, Shennen A , Mao, Michael A , Qureshi, Fahad , Kaewput, Wisit , Qureshi, Fawad , Tangpanithandee, Supawit , Krisanapan, Pajaree , Pattharanitima, Pattharawin , Acharya, Prakrati C , Nissaisorakarn, Pitchaphon , Cooper, Matthew and Cheungpasitporn, Wisit
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
Subjects
More information
Scope and Contents
Contents
Better understanding of the different phenotypes/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learni...
Alternative Titles
Full title
Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering
Authors, Artists and Contributors
Author / Creator
Vaitla, Pradeep
Jadlowiec, Caroline C
Leeaphorn, Napat
Mao, Shennen A
Mao, Michael A
Qureshi, Fahad
Kaewput, Wisit
Qureshi, Fawad
Tangpanithandee, Supawit
Krisanapan, Pajaree
Pattharanitima, Pattharawin
Acharya, Prakrati C
Nissaisorakarn, Pitchaphon
Cooper, Matthew
Cheungpasitporn, Wisit
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_1a68025869dc4ae9a1be0986b8618185
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1a68025869dc4ae9a1be0986b8618185
Other Identifiers
ISSN
2305-6320
E-ISSN
2305-6320
DOI
10.3390/medicines10040025
