In silico perturbations provide multivariate interpretability in predicting post-lung transplant outcomes

Abstract Lung transplantation is a life-saving therapy for end-stage lung disease but has the poorest survival among solid organ transplants. We analyzed standardized electronic health record (EHR) data from the United Network for Organ Sharing (UNOS) to predict one-, three-, and five-year survival...

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Autori principali:	Lucy Luo, Marcin Możejko, Nikolay S. Markov, Alec Peltekian, Suror Mohsin, Mary Carn, Phillip Cooper, Jeffrey Lysne, Anthony Joudi, Alan Betensley, Bradford C. Bemiss, Catherine Myers, Ankit Bharat, Rade Tomic, Ambalavanan Arunachalam, Ewa Szczurek, G. R. Scott Budinger, Alexander V. Misharin, Mrinalini Venkata Subramani
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2026-01-01
Serie:	Scientific Reports
Accesso online:	https://doi.org/10.1038/s41598-025-33809-7
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