AI estimation of length, weight, and head size in newborns and infants up to 6 months
Official title: Improving Artificial Intelligence-derived Algorithms for Estimating Length and Weight in NEonateS and infanTs up to 6 Months of Age
Run by Danone Asia Pacific Holdings Pte, Ltd. · NCT07514182 · Data updated 2026-11-12
This project will test whether AI can estimate babies' length, weight, and head circumference from photos or videos for infants from birth to 6 months old.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 0 Days to 6 Months |
| Sex | All |
| Enrollment | 60 (estimated) |
| Sponsor | Danone Asia Pacific Holdings Pte, Ltd. Industry-sponsored |
| Locations | 1 site (Singapore) |
| Status | Recruiting |
| Started | March 26, 2026 |
| Main results expected | October 2026 |
| Study ends | October 2026 |
| Registry record updated | April 13, 2026 |
| Trial ID | NCT07514182 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are infants from birth through 6 months admitted to the NICU/SCN at KK Women's and Children's Hospital whose parents consent to photo/video recording and clinical measurements, and who are not intubated and were born at or after 28 weeks' gestation.
✕Probably not a fit
Infants born before 28 weeks, those who are intubated, or those with structural conditions that prevent standardized length or head circumference measurement are unlikely to be eligible or to benefit from the AI approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The NEST study is a prospective observational cohort collecting paired clinical reference measurements and non-invasive two-dimensional photographs or video recordings of infants from birth up to 6 months. Trained healthcare professionals obtain standard length, weight, and head circumference during routine care and these reference measures serve as the comparison standard. Image capture occurs under real-world clinical conditions without additional contact beyond routine care and may be repeated at multiple timepoints. AI-derived estimates from the images will be compared against the clinical measurements for proof-of-concept accuracy and will not be used for clinical decision-making.
Why it matters
Potential benefit: If successful, this approach could provide a quick, non-contact way to estimate infant size that supports growth monitoring where standard equipment or close contact is limited.
How similar studies have gone: There is preliminary evidence that AI can estimate body measurements from images in older children and adults, but applying these methods to neonates and very young infants is largely novel and remains at the proof-of-concept stage.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Infants up from birth up to 6 months of postnatal age (including neonates) who have been admitted to the NICU or SCN at the time of screening 2. Parent(s) should be able to comprehend the content of the study and be willing for their child to undergo video and photo recording, and to allow access to their blood sampling results (haemoglobin) taken as part of standard clinical practice 3. Written consent from parents and/or legally acceptable representative Exclusion Criteria: 1. Infants who were born with gestational age of less than 28 weeks of gestational age 2. Infants who are intubated (i.e., endotracheal, nasotracheal intubation) at the time of screening 3. The investigator considers for any reason that the participant would not be suitable for the study 4. The participant has an existing medical condition that would prevent standardised measurement of length and/or head circumference e.g. structural abnormality of the lower limbs, orthopaedic conditions, hydrocephalus 5. Employees and/or children/family members or relatives of employees of Danone Global Research \& Innovation Center, Danone Asia Pacific Holdings Pte Ltd, or the participating site
Where it's running
-
KK Women's and Children's Hospital
Singapore, Singapore Recruiting
Study contacts
- Principal investigator: Bin Huey Quek, MBBS — KK Women's and Children's Hospital
- Study coordinator: Amilia Sng, Senior Digital Health R&I Study Manager, MSc Pharmacology
- Email: amilia.sng@danone.com
- Phone: +6594773284
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.