Prediction models for stunting at 2-years-old from Indonesian newborn population
A machine learning-based stunting prediction model effectively identifies a high-risk newborn population and enables early targeted interventions. Integration of the prediction with a prescriptive approach that considers causal pathways and evidence-based interventions is required for precise and sustainable prevention of stunting.
Authors
- Meita Dhamayanti (ORCID: https://orcid.org/0000-0001-9661-0708)
- Intan Nurma Yulita (ORCID: https://orcid.org/0000-0002-8539-3311)
- Dwi Agustian (ORCID: https://orcid.org/0000-0002-6122-0758)
- Devi Azriani (ORCID: https://orcid.org/0000-0002-7190-4766)
- Yenni Zuhairini
Institutions
- Kementerian Kesehatan Republik Indonesia (ID)
- Padjadjaran University (ID)
Publication Details
- Journal
- BMC Pediatrics
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1186/s12887-025-06096-4
- Primary Topic
- Child Nutrition and Water Access
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universitas Padjadjaran