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1,410 results on '"Yang, Xiaolin"'

16. AI-based Medical e-Diagnosis for Fast and Automatic Ventricular Volume Measurement in the Patients with Normal Pressure Hydrocephalus

Author

Zhou, Xi, Ye, Qinghao, Yang, Xiaolin, Chen, Jiakuan, Ma, Haiqin, Xia, Jun, Del Ser, Javier, and Yang, Guang

Subjects
Physics - Medical Physics, Computer Science - Computer Vision and Pattern Recognition
Abstract

Based on CT and MRI images acquired from normal pressure hydrocephalus (NPH) patients, using machine learning methods, we aim to establish a multi-modal and high-performance automatic ventricle segmentation method to achieve efficient and accurate automatic measurement of the ventricular volume. First, we extract the brain CT and MRI images of 143 definite NPH patients. Second, we manually label the ventricular volume (VV) and intracranial volume (ICV). Then, we use machine learning method to extract features and establish automatic ventricle segmentation model. Finally, we verify the reliability of the model and achieved automatic measurement of VV and ICV. In CT images, the Dice similarity coefficient (DSC), Intraclass Correlation Coefficient (ICC), Pearson correlation, and Bland-Altman analysis of the automatic and manual segmentation result of the VV were 0.95, 0.99, 0.99, and 4.2$\pm$2.6 respectively. The results of ICV were 0.96, 0.99, 0.99, and 6.0$\pm$3.8 respectively. The whole process takes 3.4$\pm$0.3 seconds. In MRI images, the DSC, ICC, Pearson correlation, and Bland-Altman analysis of the automatic and manual segmentation result of the VV were 0.94, 0.99, 0.99, and 2.0$\pm$0.6 respectively. The results of ICV were 0.93, 0.99, 0.99, and 7.9$\pm$3.8 respectively. The whole process took 1.9$\pm$0.1 seconds. We have established a multi-modal and high-performance automatic ventricle segmentation method to achieve efficient and accurate automatic measurement of the ventricular volume of NPH patients. This can help clinicians quickly and accurately understand the situation of NPH patient's ventricles., Comment: 26 pages, 4 figure, accepted by Neural Computing and Applications journal

Published
2022

29. Optimal Covariate Balancing Conditions in Propensity Score Estimation

Author

Fan, Jianqing, Imai, Kosuke, Lee, Inbeom, Liu, Han, Ning, Yang, and Yang, Xiaolin

Subjects
Statistics - Methodology, Mathematics - Statistics Theory, Statistics - Applications
Abstract

Inverse probability of treatment weighting (IPTW) is a popular method for estimating the average treatment effect (ATE). However, empirical studies show that the IPTW estimators can be sensitive to the misspecification of the propensity score model. To address this problem, researchers have proposed to estimate propensity score by directly optimizing the balance of pre-treatment covariates. While these methods appear to empirically perform well, little is known about how the choice of balancing conditions affects their theoretical properties. To fill this gap, we first characterize the asymptotic bias and efficiency of the IPTW estimator based on the Covariate Balancing Propensity Score (CBPS) methodology under local model misspecification. Based on this analysis, we show how to optimally choose the covariate balancing functions and propose an optimal CBPS-based IPTW estimator. This estimator is doubly robust; it is consistent for the ATE if either the propensity score model or the outcome model is correct. In addition, the proposed estimator is locally semiparametric efficient when both models are correctly specified. To further relax the parametric assumptions, we extend our method by using a sieve estimation approach. We show that the resulting estimator is globally efficient under a set of much weaker assumptions and has a smaller asymptotic bias than the existing estimators. Finally, we evaluate the finite sample performance of the proposed estimators via simulation and empirical studies. An open-source software package is available for implementing the proposed methods.

Published
2021

44. Development of a direct competitive enzyme‐linked immunosorbent assay for quantitation of sodium saccharin residue in food

Author

Zhao, Yajie, Wang, Mian, Zhang, Man, Yang, Xiaolin, Li, ZhenFeng, Vasylieva, Natalia, Tan, Guiyu, Wang, Baomin, and Hammock, Bruce D

Subjects
Agricultural, Veterinary and Food Sciences, Food Sciences, Chromatography, Liquid, Enzyme-Linked Immunosorbent Assay, Food Contamination, Saccharin, Sodium, Tandem Mass Spectrometry, dcELISA, food additives, mAb, sodium saccharin, Chemical Engineering, Nutrition and Dietetics, Food Science, Food sciences, Nutrition and dietetics
Abstract

Sodium saccharin is a common artificial sweetener. However, due to its possible carcinogenic effects and causing metabolic disorders, many countries have strictly regulated its use in food. In the study, we prepared a specific monoclonal antibody (mAb 2H11) using the new hapten (6-carboxylsaccharin) and developed a direct competitive enzyme-linked immunosorbent assay (dcELISA) for the screening of sodium saccharin residue in food. The half-maximum inhibition concentration (IC50 ) and working range (IC20 -IC80 , the concentrations causing 20% and 80% inhibition by sodium saccharin) were 32.5 and 6.47 to 164 ng/mL, which was 6.5 times more sensitive than the previously reported immunoassay. The average recoveries of sodium saccharin in spiked food samples detected by dcELISA ranged from 82.1% to 117%. Among 70 food samples bought in the physical stores and online, sodium saccharin residues were only detected in four samples purchased online (one canned pineapple, two winter jujube, and one kimchi). The content measured by dcELISA agreed well with those determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The developed dcELISA was proved to be a sensitive and accurate method for determining sodium saccharin in food. PRACTICAL APPLICATION: Quantitation of sodium saccharin residue in food is very necessary and important for consumers and regulatory agencies.

Published
2021

45. EFFECT OF PRE-IMPREGNATED CARBONIZED AGGREGATE ON CARBONIZATION RESISTANCE OF FULLY RECYCLED CONCRETE

Author

Yahong Ding, Xiuwen Lv, Yang Xiaolin, Zhang Meixiang, and Zou Chenglu

Subjects
fully recycled concrete, recycled aggregates, co₂ curing, carbonation depth, Clay industries. Ceramics. Glass, TP785-869
Abstract

In order to investigate the effect of treated recycled aggregates by pre-soaking calcium hydroxide (CH) combined with CO₂ curing on the carbonation resistance of fully recycled concrete. The carbonation depth of fully recycled concrete was tested at 3, 7, 14 and 28 days using the rapid carbonation method. The experimental results show that with the recycled aggregate replacement rate rising, the carbonation resistance of fully recycled concrete gradually decreases. CH pretreatment combined with CO₂ curing effectively improves the quality of the recycled aggregate, thereby improving the carbonation resistance of fully recycled concrete. The optimum effect of CO₂ curing on fully recycled concrete is achieved with the recycled fine aggregate replacement rate of 70% and the recycled coarse aggregate replacement rate of 100%. In addition, microscopic tests were used to reveal the enhancement mechanism of CH pretreatment combined with CO₂ curing increases the carbonation resistance of fully recycled concrete. Experimental data were used to fit and model the carbonation depth of fully recycled concrete formulated before and after CO₂ curing of recycled aggregates.

Published
2023
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