2022 American Transplant Congress
Distinct Phenotypes of Kidney Transplant Recipients Aged 80 Years or Older in the United States by Machine Learning Consensus Clustering
*Purpose: Our study aimed to cluster very elderly kidney transplant recipients aged 80 years and above using an unsupervised machine learning approach.*Methods: We performed consensus…2022 American Transplant Congress
Meld 3.0 for Liver Allocation: Results From the Liver Simulated Allocation Model
*Purpose: Priority on the US liver transplant waitlist is determined by the model for end-stage liver disease (MELD), a score composed of serum bilirubin, creatinine,…2022 American Transplant Congress
Evaluating the Performance and External Validity of Machine Learning-Based Prediction Models in Liver Transplantation: An International Study
*Purpose: National liver transplant (LT) registries are curated in many countries. We compared data from three national registries and developed machine learning algorithm (MLA)-based models…2022 American Transplant Congress
Computer vs Human-Based Prediction and Stratification of the Risk of Long-Term Kidney Allograft Failure
1Paris Transplant Group, Paris, France, 2NYU Langone Health, New York, NY, 3UCLA, Los Angeles, CA
*Purpose: Clinical decision-making process after transplantation is mainly driven by patient individual risk of allograft failure prediction assessed by physicians. However, this task remains difficult…2022 American Transplant Congress
A Hybrid Model Combining Survival Analysis, Knapsack Optimization and Supervised Learning to Extrapolate the Evolution of Kidney Transplantation Patients from Donors with Expanded Criteria After Controlled Circulatory Death
*Purpose: Kidney transplantation (KT) with expanded criteria donors (ECD) after controlled circulatory death (cDCD) in high-risk patients is being debated. We categorize patients via a…2021 American Transplant Congress
Poor Reliability of Karnofsky Performance Score in Kidney Transplant Candidates
Medicine, Stanford University, Palo Alto, CA
*Purpose: The Karnofsky Performance Status (KPS) Scale has been used as a proxy for frailty and as a predictor of transplant outcomes, however reliability of…2021 American Transplant Congress
Creatinine Reduction Ratio at 2 Postoperative Day as a Predicting Factor of Long-Term Outcomes After Living Donor Kidney Transplantation
*Purpose: Creatinine reduction ratio from 1 to 2 postoperative days (CRR2) under 30% has been defined as a slow graft function (SGF) and used to…2021 American Transplant Congress
Artificial Neural Network Application for MELDNa Prediction
1University of Minnesota, Minneapolis, MN, 2Cleveland Clinic Foundation, Cleveland, OH
*Purpose: The adoption of MELDNa decreased 90-days mortality on patients waiting for liver transplant (LT); however, there are no tools available to predict MELDNa trajectories…2021 American Transplant Congress
Incidence and Risk Factors for Nonmelanoma Skin Cancer in Lung Transplant Recipients
*Purpose: The purpose of this study is to identify the incidence of nonmelanoma skin cancer (NMSC) post lung transplantation and to examine the relationship between…2021 American Transplant Congress
Transplant Data Platform – An Augmented Clinical Intelligence Framework
*Purpose: UNOS, SRTR, USRDS registries are rich in patient baseline data. However, all suffer from data attrition as patients move further out post-transplant or between…
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