Oral Presentation QMSKI Conference 2024

External Validation of a Deep-Learning-Based Hip Fracture Prognosis Pipeline (#253)

Niklas Christoph Koser 1 , Eren Bora Yilmaz 1 2 , Carolina Ramirez 3 , Emma Bahroos 3 , Sharmila Majumdar 3 , Claus-C. Glüer 1
  1. i²Lab@Section Biomedical Imaging, Dept. of Radiology and Neuroradiology, University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Kiel, Schleswig-Holstein, Germany
  2. Dept. of Computer Science, Ostfalia University of Applied Sciences, Wolfenbüttel, Niedersachsen, Germany
  3. Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
Publish consent withheld
  1. Damm, Timo, et al. "Artificial intelligence-driven hip fracture prediction based on pelvic radiographs exceeds performance of DXA: the" Study of Osteoporotic Fractures"(SOF)." Journal of Bone and Min-eral Research. Vol. 37. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2022.
  2. Huang, Gao, et al. "Densely connected convolutional networks." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
  3. University of California, San Francisco, Academic Research Systems (2022). UCSF DeID CDW-OMOP. 2023-November. University of California, San Francisco. Dataset. Available through https://data.ucsf.edu/research/deid-data.