An exploratory study to collect data to build artificial intelligence derived algorithms for estimating iron status in 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 gold 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
250
Blood test will measure haemoglobin and other parameters
Images and videos of anatomical sites will be collected for AI to estimate iron status
KK Women's and Children's Hopsital
Singapore, Singapore
Srinagarind Hospital, Khon Kaen University
Khon Kaen, Thailand
Accuracy of the Iron AI in a clinic setting
Accuracy of the Iron Ai in a clinic setting, derived from: 1. The Iron AI prediction from images/videos collected 2. The gold standard blood test results
Time frame: 1 day
Parental acceptability of the Iron AI
Parental acceptability of the Iron AI assessed via the study questionnaire \[Accuracy, Usefulness, Frequency of usage, Data sharing\]
Time frame: 1 day
Investigator's (or delegates) acceptability of Iron AI
Investigators (or delegates) likelihood of using the Iron AI assessed via the study questionnaire \[Ease of taking images/videos, accuracy, frequency of use, recommendation to parents\]
Time frame: 1 day
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