An observational study in Growth, Neonates and AI (Artificial Intelligence), sponsored by Danone Asia Pacific Holdings Pte, Ltd.. Recruiting at 1 site in Singapore. Open to participants aged 0 Days to 6 Months. Per ClinicalTrials.gov, last updated 2026-04-13.
Sponsored by Danone Asia Pacific Holdings Pte, Ltd. (part of Danone) · Observational
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.
The NEST study is a prospective, observational cohort study designed to collect paired clinical reference measurements, image data, and associated clinical information to support the development and proof-of-concept evaluation of artificial intelligence (AI)-based algorithms for estimating anthropometric parameters in neonates and young infants.
Standard clinical anthropometric measurements-including infant length, weight, and head circumference-are obtained by trained healthcare professionals in accordance with site-standard clinical procedures and established neonatal measurement practices. These measurements serve as the clinical reference standard for comparison with AI-derived estimates. All reference measurements collected as part of routine clinical care during the study period may be recorded.
In parallel with clinical measurements, non-invasive image data consisting of two-dimensional photographs and/or video recordings of the infant are captured using digital imaging devices. Image capture occurs under real-world clinical conditions and does not require additional physical contact beyond routine care. Image and video data may be collected at multiple timepoints for a given participant, including repeated assessments during hospitalization or follow-up, where applicable. Image-based measurements are not used for clinical decision-making.
AI-derived estimates are compared against standard clinical reference measurements using predefined analytical accuracy and agreement metrics.
Secondary and exploratory objectives include the evaluation of AI models for additional anthropometric parameters, such as weight and head circumference, as well as assessment of the feasibility of image capture in neonatal and infant care settings. Investigator- and parent-reported perceptions related to the usability and acceptability of image-based measurement approaches are also evaluated.
For participants with laboratory test results obtained as part of routine clinical care, selected laboratory values may be recorded. In a subset of participants, additional image data may be collected to support exploratory research related to AI-based estimation of iron status. No additional laboratory testing is performed as part of the study.
Questionnaire-based feedback is collected from investigators and parents or caregivers on the image capture process and to define acceptable ranges of differences between AI-derived estimates and standard clinical measurements. and/or experiences and perceptions related to the use of AI-powered digital tools for monitoring infant growth parameters and health.
All study data are coded prior to analysis. Image data and clinical measurements are linked using study-specific participant identifiers. No facial recognition or identity verification is performed. Data are stored, processed, and analyzed in accordance with approved data protection and confidentiality measures and applicable regulatory requirements.
Danone Asia Pacific Holdings Pte, Ltd. is the lead sponsor of 29 studies on the registry; 2 are open to participants now.
Counted across the registry records on this site, refreshed daily.
The study population comprises neonates and infants from birth up to 6 months of age who are admitted to a neonatal intensive care unit (NICU) or special care nursery (SCN). Eligible participants include very preterm, moderate to late preterm, and term infants who meet the study's inclusion criteria and whose parents or legally acceptable representatives provide written informed consent. Participants are enrolled during their NICU/SCN stay and followed prospectively for the duration of their hospitalization, up to a maximum of 10 weeks. The study collects anthropometric measurements and image and video data in conjunction with routine clinical care.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
The protein in red blood cells that carries oxygen. A low level is anaemia, which can cause tiredness and breathlessness. Measured in g/dL or g/L (9 g/dL is 90 g/L).
Hemoglobin (Hb)
The protein in red blood cells that carries oxygen. A low level is anaemia, which can cause tiredness and breathlessness. Measured in g/dL or g/L (9 g/dL is 90 g/L).
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
This cohort includes neonates and infants from birth up to 6 months of age, encompassing very preterm (28-31 weeks gestation), moderate to late preterm (32-36 weeks gestation), and term infants (≥37 weeks gestation). Participants are enrolled prospectively during their stay in neonatal or infant care settings. This is an observational study; no investigational product or therapeutic intervention is administered. Study procedures involve the collection of routine clinical anthropometric measurements (length, weight, and head circumference) and the capture of photographs and/or video recordings for the development and evaluation of artificial intelligence-derived algorithms. All data are collected in conjunction with standard clinical care.
To evaluate the accuracy of the algorithm to estimate length (in cm)
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.
Time frame: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
To evaluate the mean absolute error of the algorithm to estimate weight (in kg)
The secondary outcome is the proof-of-concept accuracy of an artificial intelligence (AI)-based algorithm for estimating infant weight in a neonatal intensive care unit (NICU) or special care nursery (SCN) setting. AI-derived weight estimates (in kilograms) generated from supine images and/or videos are compared with standard clinical weight measurements obtained by trained investigators using World Health Organization (WHO)-recommended techniques. Accuracy is assessed using a composite metric that includes bias, mean absolute error, mean absolute percentage error, and the distribution of absolute percentage errors at predefined thresholds.
Time frame: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
To evaluate the mean absolute error of the algorithm to estimate head circumference (in cm)
The exploratory outcome evaluates the proof-of-concept accuracy of an artificial intelligence (AI)-based algorithm for estimating infant head circumference in a neonatal intensive care unit (NICU) or special care nursery (SCN) setting. AI-derived head circumference estimates obtained from images and/or videos are compared with standard clinical head circumference measurements performed by trained investigators using World Health Organization (WHO)-recommended techniques. Accuracy is assessed descriptively using appropriate error metrics to explore the feasibility and potential clinical utility of image-based AI estimation methods.
Time frame: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
Ease of image collection by investigator for each participant (Very Easy, Easy, Normal, Difficult, Very difficult]
Investigator's assessment on the ease of collecting the images
Time frame: Once per participant, prior to discharge from NICU/SCN (at the conclusion of study participation) [1 day]
Expected level of accuracy by the investigator for length [Less than or equal to 1 cm, less than or equal to 2 cm, less than or equal to 3 cm, less than or equal to 4 cm, less than or equal to 5 cm, more than 5 cm]
The expected level of accuracy for the anthropometric measurements for length
Time frame: Per participant, at the conclusion of study participation (prior to discharge from NICU/SCN) [1 day]
To assess the mean absolute error of the Iron algorithm to estimate hemoglobin level (mg/dl) using image recognition technology
This exploratory outcome evaluates the proof-of-concept (POC) accuracy of an artificial intelligence (AI)-based algorithm for estimating haemoglobin levels (Iron AI) in a neonatal intensive care unit (NICU) or special care nursery (SCN) setting. AI-derived haemoglobin estimates (g/dL), generated from images and/or videos collected as part of the study, are compared with haemoglobin values obtained from standard venous blood sampling performed as part of routine clinical care. Accuracy is assessed using a composite metric including bias, mean absolute error, mean absolute percentage error, and predefined percentiles of absolute percentage error. This outcome is exploratory and descriptive in nature.
Time frame: At enrolment or when routine clinical haemoglobin results become available during the NICU/SCN stay (single time point) [ 1day]
Plan to share: No — Individual participant data will not be shared. Data collected in this study will be used solely for the purposes described in the protocol and handled in accordance with applicable data protection regulations and data processing agreements.
No publications or documents are linked to this record.
Started Mar 2026 (actual). Primary completion is estimated for Oct 2026, 7 months after the start.
How these figures are worked out, and which studies are left out of them.
Eligibility is decided by the study team. Share this record with your doctor or contact the team directly.
Contact study teamGet an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Danone Asia Pacific Holdings Pte, Ltd. →