An exploratory study to collect data to build artificial intelligence derived algorithms for estimating iron status in African children
This is an exploratory, observational, pilot study that aims to build and measure the accuracy of an algorithm that estimates a child's iron status using images and/or videos, against standard venous blood sampling. Images and/or videos will be collected by healthcare professionals, together with blood test results. This data will be used to evaluate the accuracy of the algorithm and to explore potential improvements. Data on the acceptance and experience of the using the algorithm will be collected for improvements.
Study Type
OBSERVATIONAL
Enrollment
126
Blood test will measure haemoglobin and other parameters
Images and videos of anatomical sites will be collected to develop algorithms to estimate iron status
Hospital Center Régional D'abobo Félix Houphouët Boigny
Abidjan, Côte d’Ivoire
Institut National de Sante Publique
Abidjan, Côte d’Ivoire
Hôpital Mère Enfant Bingerville
Bingerville, Côte d’Ivoire
Accuracy of the Iron digital tool in estimating hemoglobin level as compared to standard blood test.
Mean absolute error (MAE), Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) will be calculated for accuracy
Time frame: 1 day
To evaluate Iron Questionnaire (IronQ)'s performance in estimating risk of iron intake deficiency as compared to dietary intake from 24-hour recall diary
Correlation Coefficient will be calculated to measure the strength and direction of association between iron intake estimated by IronQ and the 24-hour recall.
Time frame: 2 days
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