Semantic Inference on Heterogeneous E-Marketplace Activities

An electronic marketplace (e-marketplace) is a common business information space populated with many entities of different system types. Each of them has its own context of how to process activities. This leads to heterogeneous e-marketplace activities, which are difficult to make interoperable and inferred from one entity to another. This study solves this problem by proposing a concept of separation strategy and implementing it through providing a semantic inference engine with a novel inference algorithm. The solution, called the RuleXPM approach, enables one to semantically infer a next e-marketplace activity across multiple contexts/domains. Experiments show that the cross-context/cross-domain semantic inference is achievable. This paper is an understanding of many aspects related to heterogeneous activity inference

Multimodal Machine Learning for Automated ICD Coding

This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We developed separate machine learning models that can handle data from different modalities, including unstructured text, semi-structured text and structured tabular data. We further employed an ensemble method to integrate all modality-specific models to generate ICD-10 codes. Key evidence was also extracted to make our prediction more convincing and explainable. We used the Medical Information Mart for Intensive Care III (MIMIC -III) dataset to validate our approach. For ICD code prediction, our best-performing model (micro-F1 = 0.7633, micro-AUC = 0.9541) significantly outperforms other baseline models including TF-IDF (micro-F1 = 0.6721, micro-AUC = 0.7879) and Text-CNN model (micro-F1 = 0.6569, micro-AUC = 0.9235). For interpretability, our approach achieves a Jaccard Similarity Coefficient (JSC) of 0.1806 on text data and 0.3105 on tabular data, where well-trained physicians achieve 0.2780 and 0.5002 respectively.Comment: Machine Learning for Healthcare 201

Secular trend of the leading causes of death in China from 2003 to 2013

Background: To analyze the epidemiological characteristics and secular trends of the leading causes of death in China.Methods: Data on the leading causes of death was collected from the Statistical Yearbook of China. Data for 11 years, from 2003 to 2013, was analyzed by regression analysis and chi-square test.Results: The top 3 causes of death from 2009 to 2013 were cancer, cerebrovascular disease, and cardiopathy, with the role of cardiopathy increasing over time (P<0.01). The proportion of deaths related to cardio-cerebrovascular diseases in urban and rural areas increased to 41.9% and 44.8%, respectively, in 2013, and was significantly higher than that for cancer, 25.5% and 22.4% (both P<0.01). Injury and poisoning in urban or rural areas represented the fifth leading cause of death. In 2006, endocrine, nutritional, and metabolic diseases were the sixth main cause of death, with 3.3% in urban areas. The role of genito-urinary,respiratory, and digestive system diseases in urban areas and genito-urinary system diseases in rural areas decreased during this period (all P<0.05).Conclusion: Cancer, cerebrovascular disease, and cardiopathy accounted for more than 67% of all deaths from 2007 to 2013 in China, and significantly increased in proportion from 2003 to 2013.Keywords: Causes of death; China; cancer; cardiovascular diseas

Secular trend of the leading causes of death in China from 2003 to 2013.

Background: To analyze the epidemiological characteristics and secular trends of the leading causes of death in China. Methods: Data on the leading causes of death was collected from the Statistical Yearbook of China. Data for 11 years, from 2003 to 2013, was analyzed by regression analysis and chi-square test. Results: The top 3 causes of death from 2009 to 2013 were cancer, cerebrovascular disease, and cardiopathy, with the role of cardiopathy increasing over time (P<0.01). The proportion of deaths related to cardio-cerebrovascular diseases in urban and rural areas increased to 41.9% and 44.8%, respectively, in 2013, and was significantly higher than that for cancer, 25.5% and 22.4% (both P<0.01). Injury and poisoning in urban or rural areas represented the fifth leading cause of death. In 2006, endocrine, nutritional, and metabolic diseases were the sixth main cause of death, with 3.3% in urban areas. The role of genito-urinary, respiratory, and digestive system diseases in urban areas and genito-urinary system diseases in rural areas decreased during this period (all P<0.05). Conclusion: Cancer, cerebrovascular disease, and cardiopathy accounted for more than 67% of all deaths from 2007 to 2013 in China, and significantly increased in proportion from 2003 to 2013

Hydride transfer reaction catalyzed by hyperthermophilic dihydrofolate reductase is dominated by quantum mechanical tunneling and is promoted by both inter- and intramonomeric correlated motions

Simulations of hydride and deuteride transfer catalyzed by dihydrofolate reductase from the hyperthermophile Thermotoga maritima (TmDHFR) are presented. TmDHFR was modeled with its active homodimeric quaternary structure, where each monomer has three subdomains. The potential energy function was a combined quantum mechanical and molecular mechanical potential (69 atoms were treated quantum mechanically, and 35 287, by molecular mechanics). The calculations of the rate constants by ensemble-averaged variational transition state theory with multidimensional tunneling predicted that hydride and deuteride transfer at 278 K proceeded with 81 and 80% by tunneling. These percentages decreased to 50 and 49% at 338 K. The kinetic isotope effect was dominated by contributions of bound vibrations and decreased from 3.0 to 2.2 over the temperature range. The calculated rates for hydride and deuteride transfer catalyzed by the hypothetical monomer were smaller by approximately 2 orders of magnitude. At 298 K tunneling contributed 73 and 66% to hydride and deuteride transfer in the monomer. The decreased catalytic efficiency of the monomer was therefore not the result of a decrease of the tunneling contribution but an increase in the quasi-classical activation free energy. The catalytic effect was associated in the dimer with correlated motions between domains as well as within and between subunits. The intrasubunit correlated motions were decreased in the monomer when compared to both native dimeric TmDHFR and monomeric E. coli enzyme. TmDHFR and its E. coli homologue involve similar patterns of correlated interactions that affect the free energy barrier of hydride transfer despite only 27% sequence identity and different quaternary structures

Development and Validation of a Risk-Score Model for Type 2 Diabetes: A Cohort Study of a Rural Adult Chinese Population.

Some global models to predict the risk of diabetes may not be applicable to local populations. We aimed to develop and validate a score to predict type 2 diabetes mellitus (T2DM) in a rural adult Chinese population. Data for a cohort of 12,849 participants were randomly divided into derivation (n = 11,564) and validation (n = 1285) datasets. A questionnaire interview and physical and blood biochemical examinations were performed at baseline (July to August 2007 and July to August 2008) and follow-up (July to August 2013 and July to October 2014). A Cox regression model was used to weigh each variable in the derivation dataset. For each significant variable, a score was calculated by multiplying β by 100 and rounding to the nearest integer. Age, body mass index, triglycerides and fasting plasma glucose (scores 3, 12, 24 and 76, respectively) were predictors of incident T2DM. The model accuracy was assessed by the area under the receiver operating characteristic curve (AUC), with optimal cut-off value 936. With the derivation dataset, sensitivity, specificity and AUC of the model were 66.7%, 74.0% and 0.768 (95% CI 0.760-0.776), respectively. With the validation dataset, the performance of the model was superior to the Chinese (simple), FINDRISC, Oman and IDRS models of T2DM risk but equivalent to the Framingham model, which is widely applicable in a variety of populations. Our model for predicting 6-year risk of T2DM could be used in a rural adult Chinese population

Association of rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) polymorphisms in TCF7L2 with type 2 diabetes in 9,619 Han Chinese population.

AIMS: We aimed to replicate the association of the rs290487 (IVS3C/T) and rs7903146 (IVS3C/T) polymorphisms of transcription factor 7-like 2 (TCF7L2) and type 2 diabetes mellitus (T2DM) in Han Chinese people in Henan province, China. METHODS: In all, 1,842 patients with T2DM and 7,777 normal glucose-tolerant controls underwent genotyping for the T2DM-associated variants rs7903146 (IVS3C/T) and rs290487 (IVS3C/T). W performed a meta-analysis of the association of the risk alleles of rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) in TCF7L2 and T2DM in Han Chinese by combining previous studies with the present study. RESULTS: We found that T2DM was associated with the CC genotype (1.364, 1.137-1.636, p  = 0.001), the recessive model (1.457, 1.156-1.838, p  = 0.001) of rs290487 (IVS3C/T) and haplotype CC (1.116, 1.034-1.204, p  = 0.004) in Han Chinese. Moreover, our meta-analyses supported the association of the T allele (IVS3C/T) of rs7903146 (1.36, 1.24-1.48; p  = 6.404×10(-12)) and T2DM but not the C allele of rs290487 (IVS3C/T) (0.99, 0.85-1.15, p  = 0.890) in Han Chinese. We found no interactions between behavioral risk factors (smoking, alcohol drinking, and physical activity) and rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) polymorphisms. CONCLUSIONS: The CC genotype and the recessive model of the variant rs290487 (IVS3C/T) and CC haplotype of rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) in TCF7L2 may be associated with T2DM in Han Chinese people in Henan province, China

Performance of the risk-score model for a rural adult Chinese population (Chinese model) and the Chinese (simple), FINDRISC, Oman, IDRS and Framingham models with the validation dataset.

<p>Performance of the risk-score model for a rural adult Chinese population (Chinese model) and the Chinese (simple), FINDRISC, Oman, IDRS and Framingham models with the validation dataset.</p

Receiver-operating characteristic (ROC) curves for the Chinese, Chinese (simple), FINDRISC, Oman, IDRS and Framingham models with the validation dataset.

<p>Area under the ROC curve: Chinese, 0.766; Chinese (simple), 0.630; FINDRISC, 0.638; Oman, 0.673; IDRS, 0.638; Framingham, 0.745.</p