GrowthNESTNCT07514182
Improving Artificial Intelligence-derived Algorithms for Estimating Length and Weight in NEonateS and infanTs up to 6 Months of Age (NEST)
An observational study of Growth and Neonates, run by Danone Asia Pacific Holdings Pte, Ltd. at 1 site in Singapore.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 0 days to 6 months
- Conditions the study is for
- Growth, Neonates, AI (Artificial Intelligence)
- How many people
- 60 participants
- Where
- 1 siteSingapore
- Study dates
- 26 Mar 2026to Oct 2026
- How long will I take part?
- 2 Weeks
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 0 days to 6 months
- All sexes
- Child
Study population: 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.
Who may be able to join
- 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
- 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
- Written consent from parents and/or legally acceptable representative
Who cannot join
- Infants who were born with gestational age of less than 28 weeks of gestational age
- Infants who are intubated (i.e., endotracheal, nasotracheal intubation) at the time of screening
- The investigator considers for any reason that the participant would not be suitable for the study
- 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
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Amilia Sng, Senior Digital Health R&I Study Manager, MSc Pharmacology contact
Singapore1 site, 1 recruiting
- Recruiting
KK Women's and Children's Hospital
Singapore
Bin Huey Quek, MBBS
About this study
Official title: Improving Artificial Intelligence-derived Algorithms for Estimating Length and Weight in NEonateS and infanTs up to 6 Months of Age
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.
Read the detailed description
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.
- Conditions
- Growth, Neonates, AI (Artificial Intelligence)
- Keywords
- Neonates, Infants, Neonatal Growth, Infant Growth assessment, Anthropometric measurements, Infant length measurements, Infant weight measurement, Head Circumference, Artificial Intelligence, Image based assessment, Digital Health, Photographs and video recordings, Neonatal intensive care unit, Special Care nursery, Observational study, Proof of concept study, Growth monitoring
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Very preterm infants, moderate to late preterm infants, and term infants | 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
Secondary outcomes (1)
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.
Measured: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Apr 2026
- Study start26 Mar 2026
- Primary completionOct 2026 (estimated)
- Study completionOct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for GrowthStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 60 participants (estimated)
- Target duration
- 2 Weeks
Sponsor and investigators
- Lead sponsor
- Danone Asia Pacific Holdings Pte, Ltd.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- KK Women's and Children's Hospital
- Responsible party
- Sponsor
- Investigators
- Bin Huey Quek, MBBS, Principal investigator, KK Women's and Children's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07514182
- Sponsor's protocol ID
- 25REX0090391
- Acronym
- NEST
- Status last verified
- Apr 2026
- First submitted
- 26 Mar 2026
- Last updated
- 13 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- 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.
Study at a glance
From the registry record, last updated by the sponsor on 13 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Improving Artificial Intelligence-derived Algorithms for Estimating Length and Weight in NEonateS and infanTs up to 6 Months of Age
- ClinicalTrials.gov ID
- NCT07514182
- Acronym / sponsor ID
- NEST / 25REX0090391
- Conditions
- Growth, Neonates, AI (Artificial Intelligence)
- Keywords
- Neonates, Infants, Neonatal Growth, Infant Growth assessment, Anthropometric measurements, Infant length measurements, Infant weight measurement, Head Circumference
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- Danone Asia Pacific Holdings Pte, Ltd.Industry (pharma, biotech, devices)
- Collaborators
- KK Women's and Children's Hospital
- Study start
- 26 Mar 2026 (actual)
- Primary completion
- Oct 2026 (estimated)
- Study completion
- Oct 2026 (estimated)
- First posted
- 7 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 2 Weeks
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Very preterm infants, moderate to late preterm infants, and term infants | – | –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. |
Who may qualify
- Ages
- 0 days to 6 months
- Sex
- All
- Age groups
- Child
- Study population
- 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.
Key inclusion criteria (3 listed)
- 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
- 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
- Written consent from parents and/or legally acceptable representative
Key exclusion criteria (5 listed)
- Infants who were born with gestational age of less than 28 weeks of gestational age
- Infants who are intubated (i.e., endotracheal, nasotracheal intubation) at the time of screening
- The investigator considers for any reason that the participant would not be suitable for the study
- 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
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
To evaluate the accuracy of the algorithm to estimate length (in cm)
Time frame: 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.
1 secondary outcome
To evaluate the mean absolute error of the algorithm to estimate weight (in kg)
Time frame: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Apr 2026.
- Individual participant dataSharing planned: 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Amilia Sng, Senior Digital Health R&I Study Manager, MSc Pharmacology contact
Bin Huey Quek, MBBS principal investigator
KK Women's and Children's Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Growth and Neonates, run by Danone Asia Pacific Holdings Pte, Ltd. at 1 site in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 13 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Amilia Sng, Senior Digital Health R&I Study Manager, MSc Pharmacology (+6594773284, amilia.sng@danone.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To evaluate the accuracy of the algorithm to estimate length (in cm) (time frame: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Apr 2026; AzTrials last refreshed its copy on 26 Oct 2026.