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American Transplant Congress abstracts

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2022 American Transplant Congress

TOPIC: Clinical Science » Organ Inclusive

  • Development and Validation of a Machine Learning Based Virtual Biopsy System in Kidney Transplant Patients

    D. Yoo1, G. Divard1, M. Raynaud1, A. Bentall2, M. Stegall3, M. Naesens4, I. Batal5, S. Coley6, J. Gill7, M. Mengel8, L. Cornell3, M. P. Alexander2, T. Coates9, C. Legendre10, P. Reese11, c. lefaucheur12, O. Aubert1, A. Loupy1

  • Development of a Comprehensive Banff Automation System for Kidney Allograft Precision Diagnostics

    D. Yoo1, J. Gueguen1, G. Divard1, M. Raynaud1, V. Goutaudier1, M. Rabant1, M. Haas2, M. Mengel3, O. Aubert1, A. Loupy1

  • Development of Diagnostic Algorithms for Peri-Operative Error Cause and Effect Analysis in Renal Transplant Surgery

    P. Gogalniceanu1, H. Maple1, G. Papadakis1, P. Chandak1, I. Loukopoulos1, J. Olsburgh1, N. Kessaris1, F. Calder1, N. Sevdalis2, N. Mamode1

  • Differences in Post-Liver Transplant Hospitalizations by Patient Race

    K. Ross-Driscoll1, R. Lynch1, J. Wedd2, R. Patzer1

  • Direct Procurement of Heart and Lungs from a Controlled DCD Donor with Ongoing Abdominal Normothermic Regional Perfusion (aNRP) – A Synchronized Retrieval

    M. Husain1, A. Jothidasan1, C. Zeschky1, M. Osman2, M. Berman2, R. Gaurav3, A. Butler3, C. Watson3, B. Stutchfield4, I. Currie5, G. Oniscu5, J. Dunning1, U. Stock1

  • Discovery of Risk Factor Control Targets Using Machine Learning and Network Analysis for One-Year Renal Allograft Dysfunction

    Y. Lee1, M. Hong2, J. Kong3, O. Kwon4, C. Jung5, J. Yang6, M. Kim7, H. Han8, S. Nam9

  • Disparities in Low Respiratory Vaccination Among Solid Organ Transplant Recipients

    J. R. Felzer1, A. M. LeMahieu2, L. J. Finney Rutten2, Y. Juhn3, C. Wi3, R. M. Jacobson3, C. C. Kennedy1

  • Disparity In U.S. Organ Donation And Transplantation During A Global Pandemic

    J. Buggs1, K. Dhanireddy1, A. Kumar2, N. Kemmer3

  • Distinct Phenotypes of Kidney Transplant Recipients Aged 80 Years or Older in the United States by Machine Learning Consensus Clustering

    S. A. Mao1, C. Thongprayoon2, M. A. Mao3, C. C. Jadlowiec4, N. Leeaphorn5, M. Cooper6, W. Cheungpasitporn2

  • Distinct Phenotypes of Kidney Transplant Recipients with Delayed Graft Function Identified Through Machine Learning Consensus Clustering

    C. Jadlowiec1, C. Thongprayoon2, N. Leeaphorn3, W. Kaewput4, P. Pattharanitima5, M. Cooper6, W. Cheungpasitporn2

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