Publications by authors named "JiaoDong Wang"
Article Synopsis
- The study is a retrospective analysis involving 1159 patients who underwent percutaneous endoscopic lumbar discectomy (PELD) for lumbar disc herniation (LDH) between July 2014 and December 2019, aiming to predict recurrent lumbar disc herniation (rLDH) using machine learning models.
- Significant factors influencing rLDH included body mass index (BMI), facet orientation, herniation type, Modic changes, and disc calcification, with various machine learning models, such as Extreme Gradient Boost (XGBoost) and Random Forest, showing strong predictive performance.
- The findings suggest that using these machine learning models could improve decision-making and potentially reduce rLDH rates after PELD
Photocatalysis technology has been extensively adopted to abate typical air pollutants. Nevertheless, it is a challenge to develop photocatalysts aiming to simultaneously improve photocatalytic selectivity and efficiency. In this study, to improve the photocatalytic selectivity and the performance of (BiO)CO in the oxidation of NO to target products (NO /NO), we developed a novel method to construct La-doped (BiO)CO (La-BOC) for forming localized excess electrons (Ex) on (BiO)CO surface.
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