https://www.selleckchem.com/products/icg-001.html Placental growth factor (PlGF), one of the biomarkers, has a certain predictive effect on hypertensive disorders in pregnancy (HDP). To study the HDP prediction effect of different methods for variable selection and modeling for models containing PlGF. For the model containing PlGF, the appropriate range of PlGF parameters needed to be selected. Step-logistic regression and lasso were used to compare the model effect of twice range selection. The PlGF model with good predictive effect and appropriate detecting gestational age was selected for the final prediction. The effect of the model containing PlGF tested at 15-16weeks was better than the PlGF value without comprehensive screening. The sensitivity of both methods was over 92%. By comprehensive comparison, the final model of lasso method in this study was more effective. In this study, a variety of methods were used to screen models containing PlGF parameters. According to clinical needs and model effects, the optimal HDP prediction model with PlGF parameters in the second trimester of 15-26weeks of pregnancy was finally selected. In this study, a variety of methods were used to screen models containing PlGF parameters. According to clinical needs and model effects, the optimal HDP prediction model with PlGF parameters in the second trimester of 15-26 weeks of pregnancy was finally selected. In recent decades, illicit drug testing has become a high priority area in law enforcement and forensic analysis. Since patents are the largest source of technical information in the world, patent database analysis for illicit drug testing is extremely important to effectively promote the development and protection of the related intellectual property rights. In the present study, we first retrieve a database of 1732 drug detection patents using keywords and logical expressions related to the title, abstract, and claims, and subsequently discuss the current global patent stat