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Liver transplant is an essential therapy performed for severe liver diseases.
Approximate nearest neighbors: towards removing the curse of dimensionality
Indyk P, Motwani R · 1998
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Model for end-stage liver disease (MELD) and allocation of donor livers
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Longitudinal assessment of mortality risk among candidates for liver transplantation
Merion RM, Wolfe RA, Dykstra DM, Leichtman AB, Gillespie B, Held PJ · 2003
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Selection of pediatric candidates under the PELD system
McDiarmid SV, Merion RM, Dykstra DM, Harper AM · 2004
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Biggins SW, Kim WR, Terrault NA, Saab S, Balan V, Schiano T, et al · 2006
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Is MELD score sufficient to predict not only death on waiting list, but also post-transplant survival?
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Egede LE · 2006
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Abouna GM · 2008
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Hamberg K · 2008
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Fan RE, Chang KW, Hsieh CJ, Wang XR, Lin CJ · 2008
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A machine learning-based approach to prognostic analysis of thoracic transplantations
Delen D, Oztekin A, Kong ZJ · 2010
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Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al · 2011
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Revision of MELD to include serum albumin improves prediction of mortality on the liver transplant waiting list
Myers RP, Shaheen AAM, Faris P, Aspinall AI, Burak KW · 2013
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Fairness and the tyranny of potential in kidney transplantation
Kaufman SR · 2013
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Challenges of organ shortage for transplantation: solutions and opportunities
Saidi R, Kenari SH · 2014
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Kingma DP, Ba J · 2014
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Wide & deep learning for recommender systems
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Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
Shaikhina T, Lowe D, Daga S, Briggs D, Higgins R, Khovanova N · 2019
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DeepGBM: A deep learning framework distilled by GBDT for online prediction tasks
Ke G, Xu Z, Zhang J, Bian J, Liu TY · 2019
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OrganITE: Optimal transplant donor organ offering using an individual treatment effect
Berrevoets J, Jordon J, Bica I, van der Schaar M, et al · 2020
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Balancing efficiency and fairness in liver transplant access: tradeoff curves for the assessment of organ distribution policies
Bertsimas D, Papalexopoulos T, Trichakis N, Wang Y, Hirose R, Vagefi PA · 2020
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Fairness in deep learning: A computational perspective
Du M, Yang F, Zou N, Hu X · 2020
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Personalized donor-recipient matching for organ transplantation
Yoon J, Alaa A, Cadeiras M, Van Der Schaar M · 2017
Cited alongside, same era.
Machine-learning algorithms predict graft failure after liver transplantation
Lau L, Kankanige Y, Rubinstein B, Jones R, Christophi C, Muralidharan V, et al · 2017
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Fair is fair: We must re-allocate livers for transplant
Parent B, Caplan AL · 2017
Cited alongside, same era.
A convex framework for fair regression
Berk R, Heidari H, Jabbari S, Joseph M, Kearns M, Morgenstern J, et al · 2017
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DeepFM: a factorization-machine based neural network for CTR prediction
Guo H, Tang R, Ye Y, Li Z, He X · 2017
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Lightgbm: A highly efficient gradient boosting decision tree
Ke G, Meng Q, Finley T, Wang T, Chen W, Ma W, et al · 2017
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Seeing the forest for the trees: random forest models for predicting survival in kidney transplant recipients
Sapir-Pichhadze R, Kaplan B · 2020
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Fairness in machine learning: A survey
Caton S, Haas C · 2020
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Fairlearn: A toolkit for assessing and improving fairness in AI
Bird S, Dudík M, Edgar R, Horn B, Lutz R, Milan V, et al · 2020
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Predicting mortality in liver transplant candidates
Byrd J, Balakrishnan S, Jiang X, Lipton ZC · 2021
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Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis
Berrevoets J, Alaa A, Qian Z, Jordon J, Gimson AE, Van Der Schaar M · 2021
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A survey on bias and fairness in machine learning
Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A · 2021
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Machine Learning Prediction of Liver Allograft Utilization From Deceased Organ Donors Using the National Donor Management Goals Registry
Bishara AM, Lituiev DS, Adelmann D, Kothari RP, Malinoski DJ, Nudel JD, et al · 2021
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Modeling Techniques for Machine Learning Fairness: A Survey
Wan M, Zha D, Liu N, Zou N · 2021
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