Integrating radiomics with clinical data for enhanced prediction of vertebral fracture risk
This study underscores the potential of radiomics as a valuable tool for enhancing fracture risk assessment beyond traditional clinical methods. The integration of radiomics features with clinical data provides a more nuanced understanding of vertebral bone health, facilitating more accurate risk stratification and personalized management in osteoporosis care. Future research should focus on standardizing radiomics methodologies and validating these findings across diverse populations.
Authors
- Sébastien Couillard‐Després (ORCID: https://orcid.org/0000-0002-8486-6412)
- Alisia Zink
- Hamza Eren Güzel (ORCID: https://orcid.org/0000-0003-4228-0840)
- Gernot Lang (ORCID: https://orcid.org/0000-0003-0685-1909)
- Babak Saravi (ORCID: https://orcid.org/0000-0003-2298-3696)
- Sara Ülkümen
- Frank Hassel (ORCID: https://orcid.org/0000-0001-5618-9285)
- Elene Tabukashvili
Institutions
- University of Freiburg (DE)
- Paracelsus Medical University (AT)
- University Medical Center Freiburg (DE)
- Austrian Cluster for Tissue Regeneration (AT)
Publication Details
- Journal
- Frontiers in Bioengineering and Biotechnology
- Published
- 2024-11-22
- DOI
- https://doi.org/10.3389/fbioe.2024.1485364
- Citations
- 10
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.04
Funders
- Albert-Ludwigs-Universität Freiburg