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Identification of potential biological targets in sepsis based on random forest and artificial neural network models.

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Title: Identification of potential biological targets in sepsis based on random forest and artificial neural network models.
Authors: OuYang, Chenghong1, He, Huiwei1, Lin, Zhiying1 lzy1191528412@163.com
Source: Journal of Infection in Developing Countries. Apr2026, Vol. 20 Issue 4, p537-550. 15p.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 193699761
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Identification of potential biological targets in sepsis based on random forest and artificial neural network models.
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  Data: <searchLink fieldCode="AR" term="%22OuYang%2C+Chenghong%22">OuYang, Chenghong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22He%2C+Huiwei%22">He, Huiwei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Lin%2C+Zhiying%22">Lin, Zhiying</searchLink><relatesTo>1</relatesTo><i> lzy1191528412@163.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Infection+in+Developing+Countries%22">Journal of Infection in Developing Countries</searchLink>. Apr2026, Vol. 20 Issue 4, p537-550. 15p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=193699761
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      – Type: doi
        Value: 10.3855/jidc.21442
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 537
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      – TitleFull: Identification of potential biological targets in sepsis based on random forest and artificial neural network models.
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            NameFull: OuYang, Chenghong
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            NameFull: He, Huiwei
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            NameFull: Lin, Zhiying
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 20
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