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Completed

NCT Number: NCT05079776

Assessing a Length Artificial Intelligence Algorithm to Estimate Length of Children

An exploratory study to explore the possibility of using computer vision algorithms to estimate a child's length using images taken by a healthcare professional or parents.

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Key information

Conditions

Growth; Stunting, Nutritional Growth Disorders Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

0 month–18 month

Sex eligibility

All sexes

Study type

Observational

Primary location

KK Women's and Children's Hospital

Singapore, 229899

About this study

This is an exploratory, observational, pilot study that aims to evaluate the performance of a Length Artificial Intelligence (LAI) algorithm in a real world setting. Images will be collected by parents or healthcare professionals, together with physical length measurements. This data will be used to evaluate the accuracy of the algorithm and to explore potential improvements. Data on the acceptance and experience of the using the algorithm will be collected for improvements.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Children aged 0 to 18 months old.
  • Parent(s) should have access to the internet and a smartphone or tablet to complete study questionnaires, take images and upload images.
  • Parent(s) should be able to comprehend the content of the study and to complete the study questionnaires in English.
  • Written consent from parent.

Exclusion criteria

  • Parent(s) incapable of completing the study questionnaires and uploading of the images using smart phone or tablet with internet.
  • Children unable to undergo length measurement (e.g. children with structural abnormalities of the lower limbs or orthopedic conditions such as club foot, hip dysplasia, etc).

Treatment and study plan

Physical length measurement

Other

Physical length will be measured and images will be collected for AI to estimate the length

Primary outcomes

  1. Accuracy of the length AI

    Time frame: 2 days

    Accuracy of the length AI in a clinic and in a home setting, derived from:

    • The length AI prediction from images collected
    • The physical length measurement of subjects

Secondary outcomes

  1. Investigator's assessment on collection of images

    Time frame: 2 days

    Investigator's assessment on the ease of collecting the images [Very Easy, Easy, Normal, Difficult, Very Difficult]

  2. Parental acceptability of the length AI

    Time frame: 2 days

    Parental acceptability of length AI assessed via the study questionnaire [Very useful, useful, neutral, not useful, very not useful]

  3. Investigators' (or delegates) acceptability of length AI

    Time frame: 2 days

    Investigators' (or delegates) likelihood of using the length AI assessed via the study questionnaire [Very Likely, Likely, Neutral, Unlikely, Very Unlikely]

Sponsors and collaborators

Lead sponsor

Danone Asia Pacific Holdings Pte, Ltd.

Industry

Collaborators

  • KK Women's and Children's Hospital

Registry information

Official study title

Assessing the Use of a Growth Artificial Intelligence Algorithm for Estimating the leNgth of Children in Real-world Setting

Acronym: GAIN

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Oct 15, 2021
Registry last updated
Jul 27, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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