AI Performance for the Detection of Bone Fractures in Children
NCT ID: NCT05538403
Last Updated: 2022-09-13
Study Results
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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UNKNOWN
210 participants
OBSERVATIONAL
2022-05-01
2022-12-30
Brief Summary
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The objective will be to assess the AI performance for the detection of bone fractures in children aged less than 2 years old in suspected child abuse setting.
These patients benefit from a whole body radiography with a double blind reading by a "generalist" radiologist and a radiologist with expertise in child abuse. This readings will be compared with the AI results.
Hypothesis is that AI is effective for child fractures detection and could be of help especially for radiologists who are not experts in child abuse.
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* whole body radiography performed for suspected child abuse setting
* report available with a double blind reading (generalist radiologist and radiologist with expertise in child abuse)
Exclusion Criteria
* AI not applicable
0 Years
2 Years
ALL
No
Sponsors
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University Hospital, Montpellier
OTHER
Responsible Party
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Principal Investigators
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Ingrid Millet, PUPH
Role: STUDY_DIRECTOR
University Hospital, Montpellier
Locations
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University hospital
Montpellier, , France
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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RECHMPL22_0224
Identifier Type: -
Identifier Source: org_study_id
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