Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study.

Journal: PloS one
Published Date:

Abstract

BACKGROUND: Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is silent before major fragility fracture and the osteoporosis screening rate is low. Abdomen-pelvic CT (APCT) is one of the most widely conducted medical tests. Artificial intelligence and radiomics analysis have recently been spotlighted. This is the first study to evaluate the prediction performance of femoral osteoporosis using machine-learning analysis with radiomics features and APCT.

Authors

  • Hyun Kyung Lim
    Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea.
  • Hong Il Ha
    Department of Radiology, Hallym University Sacred Heart Hospital, Anyang-si, Gyeonggi-do, Republic of Korea.
  • Sun-Young Park
    Department of Radiology, Hallym University Sacred Heart Hospital, Anyang-si, Gyeonggi-do, Republic of Korea.
  • Junhee Han
    Department of Statistics and Data Science Convergence Research Center, Hallym University, Chuncheon-si, Gangwon-do, Republic of Korea.