Development and validation of a practical machine learning model to predict sepsis after liver transplantation

Chaojin Chena Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Bingcheng Chena Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Jing Yanga Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Xiaoyue Lia Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Xiaorong Penga Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Yawei Fenga Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaView further author information

Rongchang Guob Guangzhou AID Cloud Technology Co., LTD, Guangzhou, People’s Republic of ChinaView further author information

Fengyuan Zoub Guangzhou AID Cloud Technology Co., LTD, Guangzhou, People’s Republic of ChinaView further author information

Shaoli Zhoua Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaCorrespondence[email protected]
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Ziqing Heia Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of ChinaCorrespondence[email protected]
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Development and validation of a practical machine learning model to predict sepsis after liver transplantation

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