Harvard University computer scientists found that geographic areas with populations at high risk of micronutrient deficiencies can be identified using publicly available satellite data and artificial intelligence.
The method could allow for early public health interventions.
The researchers found that a combination of data, including vegetation cover, weather, and water presence, can determine where populations may suffer from a lack of iron, vitamin B12, or vitamin A.
The researchers trained their model using blood samples tested in labs.
In a study of four regions of Madagascar, the researchers found the model's predictions of regional-level micronutrient deficiency in populations outside the training datasets were as accurate, and sometimes more accurate, than estimates based on surveys by local public health officials.
From Scientific American
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA
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