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Approved Research

Improving Fracture Prediction in Patients with Osteoporosis Using Machine Learning Techniques: A Real-World, Registry-based Cohort Study

Principal Investigator: Mr Oliver Lehmann
Approved Research ID: 92242
Approval date: December 14th 2022

Lay summary

Patients with osteoporosis suffer an increase in bone fragility and fracture risk. Especially hip fractures are associated with high mortality and therapies directed against further hip fractures are associated with improved survival. To that effect, a clear need exists for identifying those who are at a high risk of suffering a fracture. We propose to apply new machine learning techniques to develop a free and publicly available computer program that will calculate each patient's risk of suffering a bone fracture in the next 2 years. Results of this project can be used by doctors when treating osteporisis patients.