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Updated: May 27, 2026

A Method to Estimate Cadaveric Femur Cortical Strains During Fracture Testing Using Digital Image Correlation
Published on: September 14, 2017
Crowd intelligence for the classification of fractures and beyond
Joseph Bernstein1, Joy S Long, Christian Veillette
1Department of Orthopedic Surgery, Veterans Hospital, Philadelphia, Pennsylvania, United States of America. orthodoc@uphs.upenn.edu
Group consensus diagnosis improves accuracy in fracture classification. Real-time internet-based consensus is feasible for medical diagnosis, enhancing diagnostic reliability.
Area of Science:
- Orthopaedic surgery
- Medical imaging analysis
- Diagnostic accuracy
Background:
- Medical diagnosis is prone to human error.
- Fracture classification diagnostic errors can potentially be reduced through consensus.
- Digital imaging and internet technologies may enable real-time diagnostic consensus.
Purpose of the Study:
- To test if group (consensus) diagnosis reduces errors in fracture classification.
- To assess the feasibility of compiling a diagnostic consensus in real-time using the internet.
Main Methods:
- Twelve orthopaedic surgeons evaluated 20 hip radiographs for femoral neck fracture displacement.
- Virtual reader groups (3 and 5 members) were formed using majority vote to assess accuracy improvement.
- A real-time internet-based group diagnosis feasibility study involved 40 volunteers responding to email requests.
Main Results:
- Individual inter-observer reliability for displacement diagnosis was a kappa coefficient of 0.69.
- Inter-observer reliability increased with group size: 0.77 for 3-member groups and 0.80 for 5-member groups.
- A 9-member consensus group was assembled in under 135.8 minutes, demonstrating feasibility of real-time internet-based diagnosis.
Conclusions:
- Consensus diagnosis shows potential for improving diagnostic accuracy in fracture classification.
- Utilizing the internet to assemble diagnostic groups in real-time is a feasible approach.
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