A Growth Artificial Intelligence Algorithm for leNgth and Weight Study

NCT06920550 | Active Not Recruiting

• 1 other identifier: 23REX0058267
• Study Type: observational
• Target: 250
• Locations: 3 countries
• Sites: 4

Brief Summary

This is a data collection and machine learning accuracy testing project that aims to a) collect training data to enhance, by machine learning, an artificial intelligence (AI) algorithm for measuring length in infants and young children and b) test the accuracy of the AI algorithm by comparing the AI predicted length with the gold standard measured length. Images and videos will be collected by care givers and healthcare professionals, together with physical length measurements. These data will be used to train the AI algorithm and to explore potential improvements. Other data to be collected is user experience feedback.

Conditions

Length; Weight

Keywords

artificial intelligence; length; weight; algorithm

Outcome Measures

Primary Outcomes (3)

• Accuracy length AI

  Accuracy of the Length AI vs length gold standard (WHO methodology with length board in cm) assessed using several different parameters: the bias (cm), agreement and reliability measures, mean absolute error (cm), mean absolute percentage error (%), percentiles of the absolute error (cm), and root mean square error (cm).

  Date of enrolment, at baseline

• Accuracy caregiver length

  Accuracy of the caregiver measured length (own preferred methodology in cm) vs gold standard measured length (WHO methodology with length board in cm), assessed by same parameters as mentioned in the first primary outcome measure.

  Date of enrolment, at baseline

• Accuracy caregiver vs AI length

  Accuracy of the caregiver measurements (self preferred methodology in cm) vs Length AI by same parameters as mentioned in the first primary outcome measure.

  Date of enrolment, at baseline

Secondary Outcomes (4)

• Accuracy weight AI

  Date of enrolment, at baseline

• Accuracy caregiver weight

  Date of enrolment, at baseline

• Ease of use tool

  Date of enrolment, at baseline

• Acceptability tool

  Date of enrolment, at baseline

Study Arms (1)

Children 0-24 months

Children aged 0-24 months of age with no structural abnormalities of the lower limbs or orthopedic conditions

Eligibility Criteria

• Age: 0 Months - 24 Months
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)
• Sampling Method: Probability Sample

Study Population

Children aged 0 to 24 months.

You may qualify if:

• Infants/young children aged 0 to 24 months old at enrolment;
• Caregiver(s) have access to the internet and a smartphone or tablet to complete questionnaires, take images and videos, and upload these;
• Written informed consent from one or both caregivers (according to local laws) or legally acceptable representative(s) aged ≥ 18 years at enrolment.

You may not qualify if:

• Children unable to undergo length or weight measurements when applying standardized techniques recommended by the WHO (e.g. infants/children with structural abnormalities of the lower limbs or orthopaedic conditions (e.g. club foot, hip dysplasia)).
• Research staff's uncertainty about the caregiver's ability or willingness to complete the study according to the instructions

Sponsors & Collaborators

• Nutricia Research: lead

Study Sites (4)

Franciscus Gasthuis

Rotterdam, Netherlands

Location

Ginemedica

Wroclaw, Poland

Location

Hospital Universitario Puerta del Mar

Cadiz, Spain

Location

Hospital Universitario de Jerez dela Frontera

Jerez de la Frontera, Spain

Location

MeSH Terms

Conditions

Body Weight

Condition Hierarchy (Ancestors)

Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 11, 2024
• First Posted: April 9, 2025
• Study Start: December 20, 2024
• Primary Completion: February 19, 2026
• Study Completion: July 31, 2026
• Last Updated: May 22, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

NL (1); ES (2); PL (1)