Using machine learning to determine the age of infant clavicle fractures
Official title: Machine learning Approaches to Radiological Dating of Infant Clavicle Fractures"
Funded at Boston Children's Hospital · NIH-10745727 · Data updated 2026-11-12
This study is looking to help doctors better determine when a baby’s collarbone fracture happened, especially in cases where child abuse might be suspected, by using smart computer technology to analyze X-ray images.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Boston Children's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | December 1, 2022 |
| Project end | November 30, 2025 |
| Funding year | 2024 |
| Award (this year) | $265,500 |
| NIH project number | 5R21HD108634-02 |
| Project ID | NIH-10745727 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include infants aged 0 to 1 year who are suspected victims of child abuse and have sustained clavicle fractures.
✕Less likely to help
Patients who do not have clavicle fractures or are older than 1 year may not benefit from this research.
What this research studies
This research focuses on improving the accuracy of dating clavicle fractures in infants, which is crucial in cases of suspected child abuse. By utilizing machine learning algorithms, the study aims to analyze skeletal survey radiographs to provide objective estimates of when these injuries occurred. This approach seeks to enhance the ability of radiologists to identify the timing of fractures, which can significantly impact legal investigations and outcomes. The research addresses a critical gap in current diagnostic practices for infant abuse cases.
Why it matters
Potential benefit: If successful, this research could lead to more accurate assessments of infant injuries, aiding in the protection of vulnerable children and improving legal proceedings related to child abuse.
How similar studies have gone: While the application of machine learning in medical imaging is gaining traction, this specific approach to dating infant fractures is relatively novel and has not been extensively tested in prior studies.
Where this research is happening
-
Boston Children's Hospital
Boston, United States Active
Researchers
- Principal investigator: Tsai, Andy — Boston Children's Hospital
- Study coordinator: Tsai, Andy
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.