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Machine Learning-Integrated Explainable Artificial Intelligence Approach for Predicting Steroid Resistance in Pediatric Nephrotic Syndrome: A Metabolomic Biomarker Discovery Study.

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Title: Machine Learning-Integrated Explainable Artificial Intelligence Approach for Predicting Steroid Resistance in Pediatric Nephrotic Syndrome: A Metabolomic Biomarker Discovery Study.
Authors: Yagin, Fatma Hilal1,2 (AUTHOR), Inceoglu, Feyza1,2 (AUTHOR), Colak, Cemil3 (AUTHOR), Alkhalifa, Amal K.4 (AUTHOR), Alzakari, Sarah A.4,5 (AUTHOR), Aghaei, Mohammadreza1,5 (AUTHOR)
Source: Pharmaceuticals (14248247). Nov2025, Vol. 18 Issue 11, p1659. 14p.
Database: Academic Search Ultimate
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  Data: Machine Learning-Integrated Explainable Artificial Intelligence Approach for Predicting Steroid Resistance in Pediatric Nephrotic Syndrome: A Metabolomic Biomarker Discovery Study.
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  Data: <searchLink fieldCode="JN" term="%22Pharmaceuticals+%2814248247%29%22">Pharmaceuticals (14248247)</searchLink>. Nov2025, Vol. 18 Issue 11, p1659. 14p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=189674630
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        Value: 10.3390/ph18111659
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        Text: English
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      – TitleFull: Machine Learning-Integrated Explainable Artificial Intelligence Approach for Predicting Steroid Resistance in Pediatric Nephrotic Syndrome: A Metabolomic Biomarker Discovery Study.
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            NameFull: Yagin, Fatma Hilal
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            NameFull: Inceoglu, Feyza
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            NameFull: Alkhalifa, Amal K.
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            NameFull: Alzakari, Sarah A.
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            – D: 01
              M: 11
              Text: Nov2025
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              Y: 2025
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