Automated machine learning-based model for the prediction of pedicle screw loosening after degenerative lumbar fusion surgery
This study aimed to use machine learning algorithms to identify critical variables and predict pedicle screw loosening after degenerative lumbar fusion surgery. A total of 552 patients who underwent primary transpedicular lumbar fixation for lumbar degenerative disease were included. The LASSO method identified key features associated with pedicle screw loosening. Patient clinical characteristics, intraoperative variables, and radiographic parameters were collected and used to construct eight machine learning models, including a training set (80% of participants) and a test set (20% of participants). The XGBoost model exhi...
Source: BioScience Trends - February 28, 2024 Category: Biomedical Science Authors: Feng Jiang Xinxin Li Lei Liu Zhiyang Xie Xiaotao Wu Yuntao Wang Source Type: research
