Transplant renal artery stenosis: utilization of machine learning to identify ancillary sonographic and doppler parameters to predict stenosis in patients with graft dysfunction
Crossref DOI link: https://doi.org/10.1007/s00261-023-03872-7
Published Online: 2023-03-22
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Blain, Yamile http://orcid.org/0000-0003-4331-7326
Alessandrino, Francesco
Scortegagna, Eduardo
Balcacer, Patricia
Text and Data Mining valid from 2023-03-22
Version of Record valid from 2023-03-22
Article History
Received: 14 December 2022
Revised: 21 February 2023
Accepted: 23 February 2023
First Online: 22 March 2023