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Hybrid feature-selection and diversity-guided stacking framework for interpretable ensemble learning: Application to COVID-19 mortality prediction.

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Title: Hybrid feature-selection and diversity-guided stacking framework for interpretable ensemble learning: Application to COVID-19 mortality prediction.
Authors: Mohtasham, Farideh1 (AUTHOR), Hashemi Nazari, Seyed Saeed2 (AUTHOR), Pourhoseingholi, Mohamad Amin3 (AUTHOR), Kavousi, Kaveh4 (AUTHOR) kkavousi@ut.ac.ir, Zali, Mohammad Reza1 (AUTHOR)
Source: PLoS ONE. 4/17/2026, Vol. 21 Issue 4, p1-28. 28p.
Database: Academic Search Ultimate
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 4/17/2026, Vol. 21 Issue 4, p1-28. 28p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=193088207
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        Value: 10.1371/journal.pone.0341198
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        Text: English
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      – TitleFull: Hybrid feature-selection and diversity-guided stacking framework for interpretable ensemble learning: Application to COVID-19 mortality prediction.
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              Text: 4/17/2026
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