AI Model Predicts Osteoporosis Risk Using Primary Care Data in Stockholm Study
A new machine learning approach can predict osteoporosis risk using routine primary care data, researchers report. The model identified healthcare visit frequency and musculoskeletal pain as strong predictors across all age groups, potentially enabling earlier intervention.
Breakthrough in Early Osteoporosis Detection
Researchers have developed a machine learning tool that can predict newly diagnosed osteoporosis using only primary care data, according to reports published in Scientific Reports. The study, conducted in the Stockholm Region, utilized Stochastic Gradient Boosting (SGB) methodology to analyze patient diagnoses and healthcare patterns preceding formal osteoporosis diagnosis. Sources indicate this approach could significantly improve early detection of the often-silent condition that affects millions worldwide.
