The NEST study is a prospective, observational research study designed to collect clinical measurements and image data to develop and evaluate artificial intelligence (AI)-derived algorithms for estimating anthropometric parameters in neonates and young infants. The study focuses on infants from birth up to 6 months of age and aims to assess the accuracy of AI-based estimations of length, weight, and head circumference using photographs and/or video recordings captured during routine clinical care. These AI-derived measurements will be compared against standard clinical measurements obtained by trained healthcare professionals in neonatal and infant care settings.
Eligibility
Sex
ALL
Min age
0 Days
Max age
6 Months
Healthy volunteers
No
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
Primary outcome measure(s)
To evaluate the accuracy of the algorithm to estimate length (in cm) — From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks The primary outcome is the proof-of-concept accuracy of an artificial intelligence (AI)-based algorithm for estimating infant length in a neonatal intensive care unit (NICU) or special care nursery (SCN) setting. AI-derived length estimates (in centimeters) obtained from supine images and/or videos are compared with standard clinical length measurements performed by trained investigators using World Health Organization (WHO)-recommended techniques. Accuracy is evaluated using a composite metric that includes bias, mean absolute error, mean absolute percentage error, and the distribution of absolute percentage errors at predefined thresholds.
Trial sites (1)
Facility
City
Region
Status
KK Women's and Children's Hospital
Singapore
Singapore
Recruiting
More Danone Asia Pacific Holdings Pte, Ltd. trials in Singapore
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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