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Predicting short-term mortality in severe cirrhosis: An interpretable machine learning model integrating routine clinical indicators.

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Title: Predicting short-term mortality in severe cirrhosis: An interpretable machine learning model integrating routine clinical indicators.
Authors: Zhang, Shun1,2 (AUTHOR), Liu, Rui2 (AUTHOR), Li, Zhengjie1,2 (AUTHOR), Pan, Tao2 (AUTHOR) pant414@163.com, Wen, Xudong2 (AUTHOR) xudongwen@cdutcm.edu.cn
Source: PLoS ONE. 3/3/2026, Vol. 21 Issue 3, p1-20. 20p.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Shun%22">Zhang, Shun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Rui%22">Liu, Rui</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zhengjie%22">Li, Zhengjie</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Tao%22">Pan, Tao</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> pant414@163.com</i><br /><searchLink fieldCode="AR" term="%22Wen%2C+Xudong%22">Wen, Xudong</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> xudongwen@cdutcm.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 3/3/2026, Vol. 21 Issue 3, p1-20. 20p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=192032859
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        Value: 10.1371/journal.pone.0328952
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              Text: 3/3/2026
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