Assessing a Length Artificial Intelligence Algorithm to Estimate Length of Children

NCT ID: NCT05079776

Last Updated: 2022-07-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-11-08

Study Completion Date

2022-06-20

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Growth; Stunting, Nutritional

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Children aged 0-18 months of age

Children aged 0-18 months of age with no structural abnormalities of the lower limbs or orthopedic conditions

Physical length measurement

Intervention Type OTHER

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

Interventions

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Physical length measurement

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

Intervention Type OTHER

Eligibility Criteria

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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).
Minimum Eligible Age

0 Months

Maximum Eligible Age

18 Months

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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KK Women's and Children's Hospital

OTHER_GOV

Sponsor Role collaborator

Danone Asia Pacific Holdings Pte, Ltd.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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KK Women's and Children's Hospital

Singapore, , Singapore

Site Status

Countries

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Singapore

References

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Chua MC, Hadimaja M, Wong J, Mukherjee SS, Foussat A, Chan D, Nandal U, Yap F. Exploring the Use of a Length AI Algorithm to Estimate Children's Length from Smartphone Images in a Real-World Setting: Algorithm Development and Usability Study. JMIR Pediatr Parent. 2024 Nov 22;7:e59564. doi: 10.2196/59564.

Reference Type DERIVED
PMID: 39576977 (View on PubMed)

Other Identifiers

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SBB20R&31696

Identifier Type: -

Identifier Source: org_study_id

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