Assessing a Length Artificial Intelligence Algorithm to Estimate Length of Children
NCT ID: NCT05079776
Last Updated: 2022-07-27
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
200 participants
OBSERVATIONAL
2021-11-08
2022-06-20
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Children aged 0-18 months of age
Children aged 0-18 months of age with no structural abnormalities of the lower limbs or orthopedic conditions
Physical length measurement
Physical length will be measured and images will be collected for AI to estimate the length
Interventions
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Physical length measurement
Physical length will be measured and images will be collected for AI to estimate the length
Eligibility Criteria
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Inclusion Criteria
2. Parent(s) should have access to the internet and a smartphone or tablet to complete study questionnaires, take images and upload images.
3. Parent(s) should be able to comprehend the content of the study and to complete the study questionnaires in English.
4. Written consent from parent.
Exclusion Criteria
2. Children unable to undergo length measurement (e.g. children with structural abnormalities of the lower limbs or orthopedic conditions such as club foot, hip dysplasia, etc).
0 Months
18 Months
ALL
Yes
Sponsors
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KK Women's and Children's Hospital
OTHER_GOV
Danone Asia Pacific Holdings Pte, Ltd.
INDUSTRY
Responsible Party
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Locations
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KK Women's and Children's Hospital
Singapore, , Singapore
Countries
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References
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Chua MC, Hadimaja M, Wong J, Mukherjee SS, Foussat A, Chan D, Nandal U, Yap F. Exploring the Use of a Length AI Algorithm to Estimate Children's Length from Smartphone Images in a Real-World Setting: Algorithm Development and Usability Study. JMIR Pediatr Parent. 2024 Nov 22;7:e59564. doi: 10.2196/59564.
Other Identifiers
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SBB20R&31696
Identifier Type: -
Identifier Source: org_study_id
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