Burke Lab

Stanford University

SOCIAL SCIENCES

Stanford · United States

NIH-funded
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NIH R01 · 2024

Machine learning in publicly available geotagged data to allow monitoring of maternal and child health

Over 95 percent of maternal and child deaths globally occur in low- and middle-income countries (LMICs) where reliable death registries are mostly unavailable and other dependable data are scarce. Moreover, within LMICs, the most disadvantaged and remote communities tend to have the highest mortality rates but the least reliable data. Knowledge on the state of maternal and child health (MCH) in LMICs relies mostly on household surveys. These expensive and time-consuming surveys cover merely a small minority (usually <2%) of all communities in a country and are (at best) carried out only every couple of years. We propose a new approach to measuring MCH indicators that would provide…

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