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A new machine learning model to predict novel trifecta achievement and validation of its prognostic significance in a large single centre series of minimally invasive partial nephrectomy

Crossref DOI link: https://doi.org/10.1016/j.acuroe.2026.501900

Published Print: 2026-06

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Farré, A. https://orcid.org/0009-0004-9573-1347
Uleri, A.

Gallioli, A.

Baboudjian, M.

Sanz, I.

Casadevall, M.

Hernández, P.

Territo, A.

Gavrilov, P.

Rodríguez Faba, O.

Huguet, J.

Gaya, J.M.

Palou, J.

Breda, A.
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Text and Data Mining valid from 2026-06-01

Text and Data Mining valid from 2026-06-01
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This article is maintained by: Elsevier

Article Title: A new machine learning model to predict novel trifecta achievement and validation of its prognostic significance in a large single centre series of minimally invasive partial nephrectomy

Journal Title: Actas Urológicas Españolas (English Edition)

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.acuroe.2026.501900

CrossRef DOI link to the associated document: https://doi.org/10.1016/j.acuro.2025.501900

Content Type: article

Copyright: © 2026 Published by Elsevier España, S.L.U. on behalf of AEU.

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