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A Growth Artificial Intelligence Algorithm for leNgth and Weight Study (GAINS)

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Nutricia

Status

Enrolling

Conditions

Length
Weight

Study type

Observational

Funder types

Industry

Identifiers

NCT06920550
23REX0058267

Details and patient eligibility

About

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.

Enrollment

250 estimated patients

Sex

All

Ages

Under 24 months old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

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

Exclusion criteria

  1. 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)).
  2. Research staff's uncertainty about the caregiver's ability or willingness to complete the study according to the instructions

Trial design

250 participants in 1 patient group

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

Trial contacts and locations

4

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Central trial contact

Danone Global Research and Innovation Center

Data sourced from clinicaltrials.gov

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