Predicting the status of 35 sustainable development goal indicators in Indian villages: a semi-supervised machine learning approach for precision public policy.
- DOI
- 10.1016/j.lansea.2026.100852
- Published
- 2026 Nov
- Container
- The Lancet regional health. Southeast Asia
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.lansea.2026.100852,
title = {Predicting the status of 35 sustainable development goal indicators in Indian villages: a semi-supervised machine learning approach for precision public policy.},
author = {Ko S and Bijral AS and Singh A and Blossom JC and Rajpal S and Joe W and Subramanian SV and Kim R},
year = {2026},
journal = {The Lancet regional health. Southeast Asia},
doi = {10.1016/j.lansea.2026.100852},
url = {https://doi.org/10.1016/j.lansea.2026.100852}
}RIS
TY - JOUR TI - Predicting the status of 35 sustainable development goal indicators in Indian villages: a semi-supervised machine learning approach for precision public policy. AU - Ko S AU - Bijral AS AU - Singh A AU - Blossom JC AU - Rajpal S AU - Joe W AU - Subramanian SV AU - Kim R PY - 2026 JO - The Lancet regional health. Southeast Asia DO - 10.1016/j.lansea.2026.100852 UR - https://doi.org/10.1016/j.lansea.2026.100852 ER -
APA
S, K., AS, B., A, S., JC, B., S, R., W, J., SV, S., & R, K. (2026). Predicting the status of 35 sustainable development goal indicators in Indian villages: a semi-supervised machine learning approach for precision public policy.. The Lancet regional health. Southeast Asia. https://doi.org/10.1016/j.lansea.2026.100852
Source records
- pubmed · retrieved 2026-09-26T01:43:04.573Z
- europe-pmc · retrieved 2026-09-26T01:43:04.587Z
- europe-pmc · retrieved 2026-09-26T01:43:04.587Z