These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

170 related articles for article (PubMed ID: 35743647)

  • 1. Distinct Phenotypes of Kidney Transplant Recipients in the United States with Limited Functional Status as Identified through Machine Learning Consensus Clustering.
    Thongprayoon C; Jadlowiec CC; Kaewput W; Vaitla P; Mao SA; Mao MA; Leeaphorn N; Qureshi F; Pattharanitima P; Qureshi F; Acharya PC; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    J Pers Med; 2022 May; 12(6):. PubMed ID: 35743647
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Use of Machine Learning Consensus Clustering to Identify Distinct Subtypes of Black Kidney Transplant Recipients and Associated Outcomes.
    Thongprayoon C; Vaitla P; Jadlowiec CC; Leeaphorn N; Mao SA; Mao MA; Pattharanitima P; Bruminhent J; Khoury NJ; Garovic VD; Cooper M; Cheungpasitporn W
    JAMA Surg; 2022 Jul; 157(7):e221286. PubMed ID: 35507356
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering.
    Thongprayoon C; Vaitla P; Jadlowiec CC; Leeaphorn N; Mao SA; Mao MA; Qureshi F; Kaewput W; Qureshi F; Tangpanithandee S; Krisanapan P; Pattharanitima P; Acharya PC; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    Medicines (Basel); 2023 Mar; 10(4):. PubMed ID: 37103780
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Differences between kidney retransplant recipients as identified by machine learning consensus clustering.
    Thongprayoon C; Vaitla P; Jadlowiec CC; Mao SA; Mao MA; Acharya PC; Leeaphorn N; Kaewput W; Pattharanitima P; Tangpanithandee S; Krisanapan P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    Clin Transplant; 2023 May; 37(5):e14943. PubMed ID: 36799718
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine Learning Consensus Clustering of Morbidly Obese Kidney Transplant Recipients in the United States.
    Thongprayoon C; Mao SA; Jadlowiec CC; Mao MA; Leeaphorn N; Kaewput W; Vaitla P; Pattharanitima P; Tangpanithandee S; Krisanapan P; Qureshi F; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    J Clin Med; 2022 Jun; 11(12):. PubMed ID: 35743357
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Differences between Kidney Transplant Recipients from Deceased Donors with Diabetes Mellitus as Identified by Machine Learning Consensus Clustering.
    Thongprayoon C; Miao J; Jadlowiec CC; Mao SA; Mao MA; Leeaphorn N; Kaewput W; Pattharanitima P; Tangpanithandee S; Krisanapan P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    J Pers Med; 2023 Jul; 13(7):. PubMed ID: 37511707
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Distinct phenotypes of kidney transplant recipients aged 80 years or older in the USA by machine learning consensus clustering.
    Thongprayoon C; Jadlowiec CC; Mao SA; Mao MA; Leeaphorn N; Kaewput W; Pattharanitima P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    BMJ Surg Interv Health Technol; 2023; 5(1):e000137. PubMed ID: 36843871
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Characteristics of Kidney Recipients of High Kidney Donor Profile Index Kidneys as Identified by Machine Learning Consensus Clustering.
    Thongprayoon C; Radhakrishnan Y; Jadlowiec CC; Mao SA; Mao MA; Vaitla P; Acharya PC; Leeaphorn N; Kaewput W; Pattharanitima P; Tangpanithandee S; Krisanapan P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    J Pers Med; 2022 Dec; 12(12):. PubMed ID: 36556213
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Clinical Phenotypes of Dual Kidney Transplant Recipients in the United States as Identified through Machine Learning Consensus Clustering.
    Tangpanithandee S; Thongprayoon C; Jadlowiec CC; Mao SA; Mao MA; Vaitla P; Leeaphorn N; Kaewput W; Pattharanitima P; Krisanapan P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    Medicina (Kaunas); 2022 Dec; 58(12):. PubMed ID: 36557033
    [No Abstract]   [Full Text] [Related]  

  • 10. Differences between Very Highly Sensitized Kidney Transplant Recipients as Identified by Machine Learning Consensus Clustering.
    Thongprayoon C; Miao J; Jadlowiec CC; Mao SA; Mao MA; Vaitla P; Leeaphorn N; Kaewput W; Pattharanitima P; Tangpanithandee S; Krisanapan P; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    Medicina (Kaunas); 2023 May; 59(5):. PubMed ID: 37241209
    [No Abstract]   [Full Text] [Related]  

  • 11. Re-assessing prolonged cold ischemia time in kidney transplantation through machine learning consensus clustering.
    Jadlowiec CC; Thongprayoon C; Tangpanithandee S; Punukollu R; Leeaphorn N; Cooper M; Cheungpasitporn W
    Clin Transplant; 2024 Jan; 38(1):e15201. PubMed ID: 38041480
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care.
    Thongprayoon C; Tangpanithandee S; Jadlowiec CC; Mao SA; Mao MA; Vaitla P; Acharya PC; Leeaphorn N; Kaewput W; Pattharanitima P; Suppadungsuk S; Krisanapan P; Nissaisorakarn P; Cooper M; Craici IM; Cheungpasitporn W
    J Pers Med; 2023 Aug; 13(8):. PubMed ID: 37623523
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Use of Machine Learning Consensus Clustering to Identify Distinct Subtypes of Kidney Transplant Recipients With DGF and Associated Outcomes.
    Jadlowiec CC; Thongprayoon C; Leeaphorn N; Kaewput W; Pattharanitima P; Cooper M; Cheungpasitporn W
    Transpl Int; 2022; 35():10810. PubMed ID: 36568137
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering.
    Thongprayoon C; Miao J; Jadlowiec C; Mao SA; Mao M; Leeaphorn N; Kaewput W; Pattharanitima P; Garcia Valencia OA; Tangpanithandee S; Krisanapan P; Suppadungsuk S; Nissaisorakarn P; Cooper M; Cheungpasitporn W
    Ren Fail; 2023; 45(2):2292163. PubMed ID: 38087474
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The UNOS renal transplant registry.
    Cecka JM
    Clin Transpl; 2001; ():1-18. PubMed ID: 12211771
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A multi-factor analysis of kidney regraft outcomes.
    Gjertson DW
    Clin Transpl; 2002; ():335-49. PubMed ID: 12971460
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Kidney transplantation in the United States.
    Cecka JM
    Clin Transpl; 2008; ():1-18. PubMed ID: 19711510
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The UNOS Scientific Renal Transplant Registry.
    Cecka JM
    Clin Transpl; 1999; ():1-21. PubMed ID: 11038622
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The OPTN/UNOS Renal Transplant Registry.
    Cecka JM
    Clin Transpl; 2005; ():1-16. PubMed ID: 17424721
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Association Between Donor-Recipient Biological Relationship and Allograft Outcomes After Living Donor Kidney Transplant.
    Husain SA; King KL; Sanichar N; Crew RJ; Schold JD; Mohan S
    JAMA Netw Open; 2021 Apr; 4(4):e215718. PubMed ID: 33847748
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.