Projektdetaljer
Beskrivelse
Ph.d. project that explores the development of machine learning and artificial intelligence methods for modelling of changes in bone mineral density over time for individuals over 50. The primary data source is nationally pooled DXA scans in the time period 2005 to 2023, for all individuals who were at least 50 years on 1.1.2010.
The dataset is enriched with a range of laboratory analyses, including bone turnover markers. The dataset is also enriched with national registry data from Statistics Denmark.
The purpose of the project is to explore the possibilities of modelling BMD trajectories for enhanced prediction of identifying individuals at risk of osteoporotic fractures.
The dataset is enriched with a range of laboratory analyses, including bone turnover markers. The dataset is also enriched with national registry data from Statistics Denmark.
The purpose of the project is to explore the possibilities of modelling BMD trajectories for enhanced prediction of identifying individuals at risk of osteoporotic fractures.
| Status | Igangværende |
|---|---|
| Effektiv start/slut dato | 01/01/2024 → 31/12/2026 |
Emneord
- Machine Learning
- Artificial Intelligence
- Osteoporosis
- Dual Energy X-ray Absorptiometry
- Bone Mineral Density
- Bone Turnover Markers
- Prediction Algorithms
- Fractures
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