Using Machine Learning to Fight Child Acute Malnutrition and Predict Weight Gain During Outpatient Treatment with a Simplified Combined Protocol
The results highlight the importance of adapting the cut-off points for weight gain to each context, as well as the practical usefulness that these techniques can have in optimizing and adapting to the treatment in humanitarian settings.
Authors
- Nassirou Ousmane
- Abdoul Aziz Gado
- Pilar Charle‐Cuéllar (ORCID: https://orcid.org/0000-0003-4784-5003)
- Noemí López‐Ejeda (ORCID: https://orcid.org/0000-0003-1310-0134)
- Luis Javier Sánchez (ORCID: https://orcid.org/0000-0002-9700-3608)
- Candela Hernández (ORCID: https://orcid.org/0000-0002-0816-7169)
Institutions
- Universidad Complutense de Madrid (ES)
- United Nations Children's Fund Niger (NE)
Publication Details
- Journal
- Nutrients
- Published
- 2024-12-06
- DOI
- https://doi.org/10.3390/nu16234213
- Citations
- 5
- Primary Topic
- Child Nutrition and Water Access
- Type
- article
- Field-Weighted Citation Impact
- 1.55
Funders
- United States Agency for International Development
- Banco Santander
- National Institute for Health and Care Research
- Foreign, Commonwealth and Development Office