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In the current study, an electronic nose (E-nose) and gas chromatography–ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow. [ABSTRACT FROM AUTHOR]

Hip fracture is a severe complication in the elderly. The affected people are at a higher risk of second fracture and death occurrence, and the best treatment for hip fractures is still being debated. Aside from the treatment, many factors, such as comorbidity conditions, may be associated with second fracture and death occurrence. This study aims to identify effective treatments and important covariates and estimate their effects on the progression of second fracture and death occurrence in hip fracture elderly patients using the semi-competing risks framework, because death dependently censors a second fracture but not vice versa. Due to the complex semi-competing risks data, performing variable selection simultaneously for second fracture and death occurrence is difficult. We propose a penalised semi-parametric copula method for semi-competing risks data. Specifically, we use separate Cox semi-parametric models for both margins and employ a copula to model the two margins' dependence. We develop a coordinate-wise optimisation algorithm that takes into account the data structure and copula function's complexities. Simulations show that the proposed method outperforms the traditional penalised marginal method. We apply the proposed method to a population-based cohort study of hip fracture elderly patients, providing new insights into their treatment and clinical management. [ABSTRACT FROM AUTHOR]

Patients with chronic diseases, such as cancer or epilepsy, are often followed through multiple stages of clinical interventions. Dynamic treatment regimes (DTRs) are sequences of decision rules that assign treatments at each stage based on measured covariates for each patient. A DTR is said to be optimal if the expectation of the desirable clinical benefit reaches a maximum when applied to a population. When there are three or more options for treatments at each decision point and the clinical outcome of interest is a time-to-event variable, estimating an optimal DTR can be complicated. We propose a doubly robust method to estimate optimal DTRs with multicategory treatments and survival outcomes. A novel blip function is defined to measure the difference in expected outcomes among treatments, and a doubly robust weighted least squares algorithm is designed for parameter estimation. Simulations using various weight functions and scenarios support the advantages of the proposed method in estimating optimal DTRs over existing approaches. We further illustrate the practical value of our method by applying it to data from the Standard and New Antiepileptic Drugs study. In this analysis, the proposed method supports the use of the new drug lamotrigine over the standard option carbamazepine. When the actual treatments match the estimated optimal treatments, survival outcomes tend to be better. The newly developed method provides a practical approach for clinicians that is not limited to cases of binary treatment options. [ABSTRACT FROM AUTHOR]

Objective To explore the prognostic factors that affect patients with advanced esophageal cancer treated with Traditional Chinese medicine (TCM). Methods A total of 72 patients with stage IV esophageal cancer were selected for analysis, and the advantaged and disadvantaged groups of TCM treatment were defined according to survival time. The log-rank method was used for the univariate analysis, the rank-sum test was used for the correlation between the syndrome type and the prognostic grouping, and the Cox proportional risk model was used for multiple factors. Results The median survival of the 72 patients with esophageal cancer was 17.9 months. The univariate analysis of the result showed that the presence of organ metastasis, the presence of lung metastasis, and the post-treatment symptom self-assessment and length of herbal medication were related to the prognosis of advanced esophageal cancer treated with TCM. The rank-sum test between the TCM syndrome elements, and survival prognosis grouping showed that the syndrome element of Qi stagnation may also affect prognosis. The result of the multi-factorial analysis showed that the factor of the duration of the TCM administration was an independent factor that affects the prognosis of advanced esophageal cancer treated with TCM. Conclusion The duration of TCM treatment affected the prognosis of patients with advanced esophageal cancer. [ABSTRACT FROM AUTHOR]

Objective To explore whether early treatment with integrated Chinese and western medicine can prolong the survival time of patients with advanced digestive tract malignant tumors using a new statistical analysis method and real-world data. Methods Based on the left truncated data, the Copula model was used to construct a joint model of the time from stage IV diagnosis to treatment and the time to overall survival. The estimated value and significance of the Copula dependence parameter, η, were obtained to evaluate the dependence strength between the two event times of interest. Results The numerical simulation showed that this method performed well when the left truncation rate was 20%. The estimated Copula dependence parameter η), in the real data analysis was 0.279 (P<0.05), indicating that there was a significant correlation between times to treatment and overall survival. Gender, the Eastern Cooperative Oncology Group score, targeted treatment, and metastatic site 1 were significant factors associated with overall survival. Conclusion The new statistical method provided valuable insights and analytical tools for the effectiveness of integrated traditional Chinese and western medicine in treating patients with advanced digestive tract malignant tumors. [ABSTRACT FROM AUTHOR]

Patients with spontaneous intracerebral hemorrhage (ICH) have poor functional outcomes. This study investigated the status of hospitalized patients with ICH based on multicenter inpatient information. We analyzed data from the hospital information systems (HISs) of 14 tertiary hospitals, including 6 Chinese medicine hospitals and 8 western hospitals from 7 provinces and 2 municipalities. The inclusion criteria were age ≥25 years and radiologically confirmed spontaneous ICH within two weeks of symptom onset. Age groups were as follows: 25–44, 45–59, 60–74, 75–89, 90 and over 90 years old. Data are presented as the proportion (%), median (interquartile range) or mean (standard deviation). Descriptive statistical analyses were conducted to analyze demographic features, lengths of hospital stay, hospitalization expenses, hematoma locations, mortality and major comorbid conditions or complications. Patients were recruited from October 2003 to September 2011. A total of 9475 inpatients were recruited from 14 Class III Grade A hospitals. Baseline characteristics included a mean age of 58 (20) years old and 37.2% female (3303). The largest number of ICH patients were in the 44–59-year-old group. The ratio of males to females in the 25–44-year-old age group was 2.36:1, which was the highest of all groups; the lowest male to female ratio was 1.56:1 in the 45–59-year-old age group. The ratios of males to females in the 60–74, 75–89 and ≥90-year-old age groups were 1.60:1, 1.62:1 and 1.64:1, respectively. The proportion of males in all age groups was higher than that of females, significantly greater in the 25–44-year-old age group (P < 0.001). The lengths of hospital stay ranged from 15 to 28 days. The hospitalization expenses of the 25–44-year-old patients were 50,000–100,000 RMB, and the costs of the remaining age groups were 10,000–20,000 RMB. Basal ganglia/thalamic hemorrhage was the most common site of ICH in different age groups. Lobar and multiple locations were higher in those aged >75 years. Hypertension was the primary comorbid condition in all age groups, and it showed a rising trend with increasing age. The second most common comorbidity in the 25–44-year-old age group was vascular abnormality, while in the other age groups, comorbidities included cerebral infarction, dyslipidemia, coronary heart disease, diabetes mellitus and arrhythmia. Mortality increased with age; mortality for those under the age of 74 years fluctuated between 4.09% and 5.93%, whereas in those in the 75–89 and ≥90-year-old age groups, mortality was 13.34% and 34.09%, respectively. As age increased, the length of hospital stay, financial burden and mortality due to ICH increased. Different age groups had different distributions of neuroimaging features, major comorbid conditions or complications. [ABSTRACT FROM AUTHOR]

Background: In China, the basic insurance system consists of three schemes: the UEBMI (Urban Employee Basic Medical Insurance), URBMI (Urban Resident Basic Medical Insurance), and NCMS (New Cooperative Medical Scheme), across which significant differences have been observed. Since 2009, the central government has been experimenting with consolidating these schemes in selected areas. This study examines whether differences still exist across schemes after the consolidation. Methods: A survey was conducted in the city of Suzhou, collecting data on subjects 45 years old and above with at least one inpatient or outpatient treatment during a period of twelve months. Analysis on 583 subjects was performed comparing subjects’ characteristics across insurance schemes. A resampling-based method was applied to compute the predicted gross medical cost, OOP (out-of-pocket) cost, and insurance reimbursement rate. Results: Subjects under different insurance schemes differ in multiple aspects. For inpatient treatments, subjects under the URBMI have the highest observed and predicted gross and OOP costs, while those under the UEBMI have the lowest. For outpatient treatments, subjects under the UEBMI and URBMI have comparable costs, while those under the NCMS have much lower costs. Subjects under the NCMS also have a much lower reimbursement rate. Conclusions: Differences still exist across schemes in medical costs and insurance reimbursement rate post-consolidation. Further investigations are needed to identify the causes, and interventions are needed to eliminate such differences. [ABSTRACT FROM AUTHOR]

In this paper, we propose an adaptive stochastic gradient boosting tree for classification studies with imbalanced data. The adjustment of cost-sensitivity and the predictive threshold are integrated together with a composite criterion into the original stochastic gradient boosting tree to deal with the issues of the imbalanced data structure. Numerical study shows that the proposed method can significantly enhance the classification accuracy for the minority class with only a small loss in the true negative rate for the majority class. We discuss the relation of the cost-sensitivity to the threshold manipulation using simulations. An illustrative example of the analysis of suboptimal health-state data in traditional Chinese medicine is discussed. [ABSTRACT FROM AUTHOR]

Clustering algorithms are important methods widely used in mining data streams because of their abilities to deal with infinite data flows. Although these algorithms perform well to mining latent relationship in data streams, most of them suffer from loss of cluster purity and become unstable when the inputting data streams have too many noisy variables. In this article, we propose a clustering algorithm to cluster data streams with noisy variables. The result from simulation shows that our proposal method is better than previous studies by adding a process of variable selection as a component in clustering algorithms. The results of two experiments indicate that clustering data streams with the process of variable selection are more stable and have better purity than those without such process. Another experiment testing KDD-CUP99 dataset also shows that our algorithm can generate more stable result. [ABSTRACT FROM AUTHOR]

It is well known that statistical classifiers trained from imbalanced data lead to low true positive rates and select inconsistent significant variables. In this article, an improved method is proposed to enhance the classification accuracy for the minority class by differentiating misclassification cost for each group. The overall error rate is replaced by an alternative composite criterion. Furthermore, we propose an approach to estimate the tuning parameter, the composite criterion, and the cut-point simultaneously. Simulations show that the proposed method achieves a high true positive rate on prediction and a good performance on variable selection for both continuous and categorical predictors, even with highly imbalanced data. An illustrative example of the analysis of the suboptimal health state data in traditional Chinese medicine is discussed to show the reasonable application of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, we introduce the L1 regularized support vector machine (L1-SVM) as an effective feature selection technique into the modeling of financial early warning system (EWS), for the purpose of establishing compact financial EWSs for Chinese-listed companies. By introducing LASSO penalty into the SVM framework, the L1-SVM is a capable methodology to select causative features in classification problem. We evaluate the feature selection performance of L1-SVM under different circumstances through numerical simulations and find it suitable for selecting features for financial EWS. In the real study, we establish four financial EWSs with features selected by L1-SVM and compare them with those trained with full features. The empirical result illustrates that our EWSs, with only minority of features, outperform significantly than full ones in the respect of generalization performance, which indicates the feasibility of L1-SVM in real applications. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

To improve the gelling property of konjac gum (KGM) and enhance the application value of Abelmoschus manihot (L.) medic gum (AMG), a novel type of gel was prepared using KGM and AMG in this study. The effects of AMG content, heating temperature and salt ions on the characteristics of KGM/AMG composite gels were studied by Fourier transform infrared spectroscopy (FTIR), zeta potential, texture analysis and dynamic rheological behavior analysis. The results indicated that the AMG content, heating temperature and salt ions could affect the gel strength of KGM/AMG composite gels. Hardness, springiness, resilience, G′, G* and η* of KGM/AMG composite gels increased when AMG content increased from 0 to 2.0 %, but they decreased when AMG increased from 2.0 % to 3.5 %. High-temperature treatment significantly enhanced the texture and rheological properties of KGM/AMG composite gels. The addition of salt ions reduced the zeta potential absolute value and weakened the texture and rheological properties of KGM/AMG composite gels. Furthermore, the KGM/AMG composite gels could be classified as non-covalent gels. The non-covalent linkages included hydrogen bonding and electrostatic interactions. These findings would help understand the properties and formation mechanism of KGM/AMG composite gels and help improve the application value of KGM and AMG. [ABSTRACT FROM AUTHOR]