Bambha K, Shingina A, Dodge JL, O’Connor K, Dunn S, Prinz J, Pabst M, Nilles K, Sibulesky L, Biggins SW. Solid organ donation after death in the United States: data-driven messaging to encourage potential donors. Am J Transplant. 2020;20:1642–9.

Article  PubMed  Google Scholar 

Dogar AW, Ullah K, Ochani S, Ahmad HB. Evolving liver transplantation in Pakistan: future challenges. Ann Med Surg. 2022;82:104669.

Article  Google Scholar 

Erazo I, Goldsman D, Keskinocak P, Sokol J. A simulation-optimization framework to improve the organ transplantation offering system. In: 2022 winter simulation conference (WSC). IEEE; 2022. p. 1009–20.

Chapter  Google Scholar 

Gotlieb N, Azhie A, Sharma D, Spann A, Suo NJ, Tran J, Orchanian-Cheff A, Wang B, Goldenberg A, Chassé M, Cardinal H. The promise of machine learning applications in solid organ transplantation. Npj Digit Med. 2022;5:89.

Article  PubMed  PubMed Central  Google Scholar 

Lebret A. Allocating organs through algorithms and equitable access to transplantation—a European human rights law approach. J Law Biosci. 2023;10:lsad0044.

Article  Google Scholar 

Dirchwolf M, Becchetti C, Gschwend SG, Toso C, Dutkowski P, Immer F, Beyeler F, Rossi S, Schropp J, Dufour JF, Banz V. The MELD upgrade exception: a successful strategy to optimize access to liver transplantation for patients with high waiting list mortality. HPB. 2022;24:1168–76.

Article  PubMed  Google Scholar 

Silva-Aravena F, Delafuente HN, Astudillo CA. A novel strategy to classify chronic patients at risk: a hybrid machine learning approach. Math. 2022;10:3053.

Article  Google Scholar 

Bayat S, Abtahi AR, Damghani KK, Zenouz RY. Identification and prioritization of key factors in the liver transplantation system using DEMATEL-modified ANP method. Razavi Int J Med. 2023;11:21–6.

Google Scholar 

Szugye NA, Zafar F, Ollberding NJ, Villa C, Lorts A, Taylor MD, Morales DL, Moore RA. A novel method of donor-recipient size matching in pediatric heart transplantation: a total cardiac volume-predictive model. JHLT. 2021;40:158–65.

Google Scholar 

Guijo-Rubio D, Briceño J, Gutiérrez PA, Ayllón MD, Ciria R, Hervás-Martínez C. Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation. PLoS ONE. 2021;16:e0252068.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dueñas-Jurado JM, Gutiérrez PA, Casado-Adam A, Santos-Luna F, Salvatierra-Velázquez A, Cárcel S, Robles-Arista CJC, Hervás-Martínez C. New models for donor-recipient matching in lung transplantations. PLoS ONE. 2021;16:e0252148.

Article  PubMed  PubMed Central  Google Scholar 

Bayer F, Dorent R, Cantrelle C, Legeai C, Kerbaul F, Jacquelinet C. France’s new lung transplant allocation system: combining equity with proximity by optimizing geographic boundaries through the supply/demand ratio. Transpl Int. 2022;35:10049.

Article  PubMed  PubMed Central  Google Scholar 

Al-Ebbini LM. An efficient allocation for lung transplantation using ant colony optimization. Intell Autom Soft Co. 2023;35:1971.

Article  Google Scholar 

Salimian S, Mousavi SM, Turskis Z. Transportation mode selection for organ transplant networks by a new multi-criteria group decision model under interval-valued intuitionistic fuzzy uncertainty. Inform. 2023;34:337–55.

Google Scholar 

Gnanasambandhan S, Balasubramanian V. HEL-MCNN: hybrid extreme learning modified convolutional neural network for allocating suitable donors for patients with minimized waiting time. Expert Syst Appl. 2023;232:120673.

Article  Google Scholar 

Vaulet T, Al-Memar M, Fourie H, Bobdiwala S, Saso S, Pipi M, Stalder C, Bennett P, Timmerman D, Bourne T, De Moor B. Gradient boosted trees with individual explanations: an alternative to logistic regression for viability prediction in the first trimester of pregnancy. Comput Methods Programs Biomed. 2022;213:106520.

Article  PubMed  PubMed Central  Google Scholar