Assessing a Length Artificial Intelligence Algorithm to Estimate Length of Children

Growth; Stunting, Nutritional Clinical Trial

— GAIN  

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05079776
• Other study ID #: SBB20R&31696
• Status: Completed
• Start date: November 8, 2021
• Est. completion date: June 20, 2022

Study information

• Verified date: July 2022
• Source: Danone Asia Pacific Holdings Pte, Ltd.
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 200
• Est. completion date: June 20, 2022
• Est. primary completion date: March 8, 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A to 18 Months

Eligibility

Inclusion Criteria:

1. Children aged 0 to 18 months old.

2. Parent(s) should have access to the internet and a smartphone or tablet to complete study questionnaires, take images and upload images.

3. Parent(s) should be able to comprehend the content of the study and to complete the study questionnaires in English.

4. Written consent from parent.

Exclusion Criteria:

1. Parent(s) incapable of completing the study questionnaires and uploading of the images using smart phone or tablet with internet.

2. 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).

Related Conditions & MeSH terms

• Growth Disorders
• Growth; Stunting, Nutritional

Intervention

Other:
• Physical length measurement
Physical length will be measured and images will be collected for AI to estimate the length

Locations

Country	Name	City	State
Singapore	KK Women's and Children's Hospital	Singapore

Sponsors (2)

Lead Sponsor	Collaborator
Danone Asia Pacific Holdings Pte, Ltd.	KK Women's and Children's Hospital

Country where clinical trial is conducted

Singapore, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of the length AI	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	2 days
Secondary	Investigator's assessment on collection of images	Investigator's assessment on the ease of collecting the images [Very Easy, Easy, Normal, Difficult, Very Difficult]	2 days
Secondary	Parental acceptability of the length AI	Parental acceptability of length AI assessed via the study questionnaire [Very useful, useful, neutral, not useful, very not useful]	2 days
Secondary	Investigators' (or delegates) acceptability of length AI	Investigators' (or delegates) likelihood of using the length AI assessed via the study questionnaire [Very Likely, Likely, Neutral, Unlikely, Very Unlikely]	2 days