Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques.

<h4>Background</h4>Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating better predictive models for risk stratification. As traditional models often fail to capture the complex, non-linear patterns underlying bleeding...

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Autori principali:	Taiichi Wakiya, Yukihiro Sanada, Noriki Okada, Yuta Hirata, Toshio Horiuchi, Takahiko Omameuda, Yasuharu Onishi, Yasunaru Sakuma, Hironori Yamaguchi, Yoshihiro Sasaki, Naohiro Sata
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Public Library of Science (PLoS) 2026-01-01
Serie:	PLoS ONE
Accesso online:	https://doi.org/10.1371/journal.pone.0326000
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