About this document
2025 03 28 25324832v1 Full by 205542002 is a document available to read on EtoBox.
This preprint discusses a study on automated Cobb angle measurement to identify undiagnosed scoliosis in the UK Biobank, involving 33,889 participants. The study found that a significant portion of the population has undiagnosed scoliosis, with a higher prevalence in females and associations between Cobb angle and various health conditions. The research highlights the potential of using deep learning algorithms for large-scale analysis of spinal conditions using MRI data.
- Author
- 205542002
- Language
- EN