Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA: a multicentre study
Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA: a multicentre study
Toshihiro Nakayama, Jenny H. Pan, Yuki Bekki, K. Bozhilov et al.
Citations
3 citations
Journal
The Lancet Digital Health
Topics
Organ Transplantation Techniques and Outcomes
Field-Weighted Citation Impact (FWCI)
6.02
article
Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA: a multicentre study
Toshihiro Nakayama, Jenny H. Pan, Yuki Bekki, K. Bozhilov, Yuzuru Sambommatsu, Kazunari Sasaki, Daiki Soma, Chase J. Wehrle, Yutaka Endo, Koji Tomiyama, Daniel J. Firl, Masaru Kubota, Masato Fujiki, Magdy Attia, Marc L. Melcher, Jiro Kusakabe, Rintaro Yanagawa, Kazuhiro Iwadoh
article en
3 citations
Abstract
No abstract available for this paper.
Publication Tag
The Lancet Digital HealthVol. 7(10)
Institutions
Cleveland Clinic (US), Duke University (US), Virginia Commonwealth University (US), Kyoto University (JP), Columbia University Irving Medical Center (US), University of Rochester Medical Center (US), University of Florida (US), Andover Eye Associates (US), Stanford Medicine (US), Mita Hospital (JP), Florida College (US), Stanford University (US)