Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children

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Publication Details

Journal
˜The œItalian Journal of Pediatrics/Italian journal of pediatrics
Published
2025-03-24
DOI
https://doi.org/10.1186/s13052-025-01892-1
Citations
1
Primary Topic
Child Nutrition and Water Access
Type
article
Field-Weighted Citation Impact
1.12
Controls
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article

Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children

Belayneh Endalamaw Dejene, Gizachew Mulu Setegn
1 citations
˜The œItalian Journal of Pediatrics/Italian journal of pediatrics
Child Nutrition and Water Access
1.12
article

Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children

Belayneh Endalamaw Dejene, Gizachew Mulu Setegn
article en
1 citations

Abstract

No abstract available for this paper.
˜The œItalian Journal of Pediatrics/Italian journal of pediatricsVol. 51(1)
Debark University (ET), University of Gondar (ET)
Zero hunger
Openalex Percentile: Top 26%
Child Nutrition and Water Access
1.12
DOIOpen Access PDFOpenAlex
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Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children — Belayneh Endalamaw Dejene, Gizachew Mulu Setegn · ˜The œItalian Journal of Pediatrics/Italian journal of pediatrics (2025) | TGRS Research Map | TGRS