Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys
Machine Learning
2020-12-01 v1 Databases
Abstract
Existing datasets available to address crucial problems, such as child mortality and family planning discontinuation in developing countries, are not ample for data-driven approaches. This is partly due to disjoint data collection efforts employed across locations, times, and variations of modalities. On the other hand, state-of-the-art methods for small data problem are confined to image modalities. In this work, we proposed a data-level linkage of disjoint surveys across Sub-Saharan African countries to improve prediction performance of neonatal death and provide cross-domain explainability.
Keywords
Cite
@article{arxiv.2011.12707,
title = {Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys},
author = {Girmaw Abebe Tadesse and Celia Cintas and Skyler Speakman and Komminist Weldemariam},
journal= {arXiv preprint arXiv:2011.12707},
year = {2020}
}
Comments
3 pages