National Comprehensive Cancer Network （NCCN） riSK classification in predicting biochemical recurrence after radical prostatectomy： a retrospective cohort study in Chinese prostate cancer patients

This study aimed to assess the role of the National Comprehensive Cancer Network （NCCN） risk classification in predicting biochemical recurrence （BCR） after radical prostatectomy （RP） in Chinese prostate cancer patients. We included a consecutive cohort of 385 patients with prostate cancer who underwent RP at Fudan University Shanghai Cancer Center （Shanghai, China） from March 2011 to December 2014. Gleason grade groups were applied at analysis according to the 2014 International Society of Urological Pathology Consensus. Risk groups were stratified according to the NCCN Clinical Practice Guidelines in Oncology： Prostate Cancer version 1, 2017. All 385 patients were divided into BCR and non-BCR groups. The clinicopathological characteristics were compared using an independent sample t-test, Chi-squared test, and Fisher＇s exact test. BCR-free survival was compared using the log-rank test and multivariable Cox proportional hazard analysis. During median follow-up of 48 months （range： 1-78 months）, 31 （8.05%） patients experienced BCR. The BCR group had higher prostate-specific antigen level at diagnosis （46.54 ± 39.58 ng m1-1 vs 21.02 ± 21.06 ng ml-1, P= 0.001）, more advanced pT stage （P= 0.002）, and higher pN1 rate （P〈 0.001）. NCCN risk classification was a significant predictor of BCR {P = 0.0006） and BCR-free survival （P = 0.003） after RP. As NCCN risk level increased, there was a significant decreasing trend in BCR-free survival rate （Ptrend = 0.0002）. This study confirmed and validated that NCCN risk classification was a significant predictor of BCR and BCR-free survival after RP.

The Distributed Representation for Societal Risk Classification toward BBS Posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.

A high‑dimensionality‑trait‑driven learning paradigm for high dimensional credit classification

To solve the high-dimensionality issue and improve its accuracy in credit risk assessment,a high-dimensionality-trait-driven learning paradigm is proposed for feature extraction and classifier selection.The proposed paradigm consists of three main stages:categorization of high dimensional data,high-dimensionality-trait-driven feature extraction,and high-dimensionality-trait-driven classifier selection.In the first stage,according to the definition of high-dimensionality and the relationship between sample size and feature dimensions,the high-dimensionality traits of credit dataset are further categorized into two types:100<feature dimensions<sample size,and feature dimensions≥sample size.In the second stage,some typical feature extraction methods are tested regarding the two categories of high dimensionality.In the final stage,four types of classifiers are performed to evaluate credit risk considering different high-dimensionality traits.For the purpose of illustration and verification,credit classification experiments are performed on two publicly available credit risk datasets,and the results show that the proposed high-dimensionality-trait-driven learning paradigm for feature extraction and classifier selection is effective in handling high-dimensional credit classification issues and improving credit classification accuracy relative to the benchmark models listed in this study.

Risks Matrixes Risks Assessment Tools of Small and Medium-Sized Enterprises： The Case of Latvia

The enterprises need to assess the risk dynamic of financial instability and its impact on small and medium-sized enterprises＇ development, because it is important for enterprises to extend commercial activity and to open a new structural subdivision. We have researched types of risks, their identification, classification, and assessment possibilities in activities of small and medium-sized enterprises. We have used our own algorithm of identification, classification, and assessment of enterprises＇ risks. The goal of this research is to study the economic and financial risks＇ impact on small and medium-sized enterprises＇ development in Latvia. For study purpose, we have carried out the questionnaire of representative small and medium-sized enterprises about the economic and financial risks＇ impact on enterprises＇ development in Latvia. We have created classification of Latvian services sectors＇ economic and financial risks in the period from 2011 to 2012. Those risks have been included in the questionnaire. The risks matrix is a quantitative assessment tool of risks. We have created Latvian service sector economic and financial risks matrix. We have arranged risks by their sizes of possible losses for enterprises. For each risk has been assessed its probability of realization. We have created Latvian accommodations （hotel） and food services technological process risks map. Several parts of the risk map （segments） make it possible to assess each type of the risk separately in its segment. Risks matrix can be used to choose enterprises＇ strategy of risk management. Enterprise＇s strategy of risk management is developed by analysing zones of risk level.

Assessment of typhoon storm surge disaster scale based on expansion model

The South China Sea suffers strongly from the typhoon storm surge disasters in China,and its northern coastal areas are facing severe risks.Therefore,it is necessary and urgent to establish an assessment system for rating typhoon storm surge disaster.We constructed an effective and reliable rating assessment system for typhoon storm surge disaster based on the theories of over-threshold,distribution function family,and composite extreme value.The over-threshold sample was used as the basis of data analysis,the composite extreme value expansion model was used to derive the design water increment,and then the disaster level was delineated based on the return period level.The results of the extreme value model comparison show that the Weibull-Pareto distribution is more suitable than the classical extreme value distribution for fitting the over-threshold samples.The results of the return period projection are relatively stable based on different analysis samples.Taking the 10 typhoon storm surges as examples,they caused landfall in the Guangdong area in the past 10 years.The results of the assessment ranking indicate that the risk levels based on the return period levels obtained from different distributions are generally consistent.When classifying low-risk areas,the classification criteria of the State Oceanic Administration,China(SOA,2012)are more conservative.In the high-risk areas,the results of the assessment ranking based on return period are more consistent with those of the SOA.

The role of drug utilization evaluation in medical sciences

Background:Drug utilization evaluation(DUE)is defined by the World Health Organization(WHO)and focuses on the medical,social,and economic consequences of pharmaceutical marketing,distribution,prescribing,and usage in society.The WHO recommends a physician to every 1000 people.According to the recent data from the Health Ministry in 2019,in which 1.16 million doctors are of active population with just 80%,or 0.9 million,practicing.As a result,a ratio of 0.68 doctors for every 1000 people,which is much below as per the WHO reports.This article describes history,types,WHO guidelines,need and purpose of DUE.Objective:The main aim of this paper is to provide information about the rational use of medication in outpa­tient and inpatient department with special emphasis of DUEs.It also provides awareness directly to healthcare professionals,researchers,academicians,pharmacist and nurses to reduce the irrationality of medicines.Methods:The method used to compile this review information gathered from websites,Google scholar,PubMed,Research gate,and studies published on DUE from July 20 to Oct 22 were included as source of information.Results:We studied more than 35 published study on DUE,that reveals most of the physicians prescribed branded drugs not generic drugs,but WHO prescribing indicator allows to prescribe generic drugs in the hospital pharmacy to maintain better inventory control.It may also help to prevent pharmacist misunderstanding during dispensing.Conclusion:The use of generic prescription names avoids the possibility of medication product duplication and lowers patient costs.It is important to remember that incorrect medication prescriptions have impact on both patients and their family members.WHO indicators identify irrational prescribing behaviours to make therapy more rational and cost-effective.

Software Metric Analysis of Open-Source Business Software

Over the past decade, open-source software use has grown. Today, many companies including Google, Microsoft, Meta, RedHat, MongoDB, and Apache are major participants of open-source contributions. With the increased use of open-source software or integration of open-source software into custom-developed software, the quality of this software component increases in importance. This study examined a sample of open-source applications from GitHub. Static software analytics were conducted, and each application was classified for its risk level. In the analyzed applications, it was found that 90% of the applications were classified as low risk or moderate low risk indicating a high level of quality for open-source applications.

AN EMPIRICAL FEASIBILITY STUDY OF SOCIETAL RISK CLASSIFICATION TOWARD BBS POSTS

Societal risk classification is the fundamental issue for online societal risk monitoring. To show the challenge and feasibility of societal risk classification toward BBS posts, an empirical analysis is implemented in this paper. Through effectiveness analysis, Support Vector Machine based on Bag-Of-Words （BOW-SVM） is adopted for challenge validation, and the distributed document embeddings of BBS posts generated by Paragraph Vector are applied to feasibility study. Based on BOW-SVM, cross-validations of BBS posts labeled by different groups and annotators are conducted. The big fluctuation of cross-validation results indicates the differences of individual risk perceptions, which brings more challenges to societal risk classification. Furthermore, based on the distributed document embeddings of BBS posts, the pairwise similarities of more than 300 thousands BBS posts from different societal risk categories are compared. The higher similarities of BBS posts in the same societal risk category reveal that BBS posts in the same societal risk category share more features than BBS posts in different categories, which manifests the feasibility of societal risk classification of BBS posts, and also reflects the possibility to improve the performance of societal risk monitoring.

Efficacy of endoscopic ultrasound in the evaluation of small gastrointestinal stromal tumors

BACKGROUND Gastrointestinal stromal tumors(GISTs)with a diameter of<2 cm are called small GISTs.Currently,endoscopic ultrasound(EUS)is widely used as a regular followup method for GISTs,which can also provide a preliminary basis for judging the malignancy potential of lesions.However,there are no studies on the accuracy of EUS to assess the malignant potential of small GISTs.AIM To evaluate the efficacy of EUS in the diagnosis and risk assessment of small GISTs.METHODS We collected data from patients with small GISTs who were admitted to Shengjing Hospital of China Medical University between October 2014 and July 2019.The accurate diagnosis and risk classifications of patients were based on the pathological assessment according to the modified National Institute of Health criteria after endoscopic resection or laparoscopic surgery.Preoperative EUS features(marginal irregularity,cystic changes,homogeneity,ulceration,and strong echogenic foci)were retrospectively analyzed.The assessment results based on EUS features were compared with the pathological features.RESULTS A total of 256 patients(69 men and 187 women)were enrolled.Pathological results included 232,16,7,and 1 very low-,low-,intermediate-,and high-risk cases,respectively.The most frequent tumor location was the gastric fundus(78.1%),and mitoses were calculated as>5/50 high power field in 8(3.1%)patients.Marginal irregularity,ulceration,strong echo foci,and heterogeneity were detected in 1(0.4%),2(0.8%),22(8.6%),and 67(65.1%)patients,respectively.However,cystic changes were not detected.Tumor size was positively correlated with the mitotic index(P<0.001).Receiver operating curve analysis identified 1.48 cm as the best cut-off value to predict malignant potential(95%confidence interval:0.824–0.956).EUS heterogeneity with tumor diameters>1.48 cm was associated with higher risk classification(P<0.05).CONCLUSION Small GISTs(diameters>1.48 cm)with positive EUS features should receive intensive surveillance or undergo endoscopic surgery.EUS and dissection are efficient diagnostic and therapeutic approaches for small GISTs.

ENSEMBLE OF MULTIPLE kNN CLASSIFIERS FOR SOCIETAL RISK CLASSIFICATION

Societal risk classification is a fundamental and complex issue for societal risk perception. To conduct societal risk classification, Tianya Forum posts are selected as the data source, and four kinds of representations： string representation, term-frequency representation, TF-IDF representation and the distributed representation of BBS posts are applied. Using edit distance or cosine similarity as distance metric, four k-Nearest Neighbor （kNN） classifiers based on different representations are developed and compared. Owing to the priority of word order and semantic extraction of the neural network model Paragraph Vector, kNN based on the distributed representation generated by Paragraph Vector （kNN-PV） shows effectiveness for societal risk classification. Furthermore, to improve the performance of societal risk classification, through different weights, kNN-PV is combined with other three kNN classifiers as an ensemble model. Through brute force grid search method, the optimal weights are assigned to different kNN classifiers. Compared with kNN-PV, the experimental results reveal that Macro-F of the ensemble method is significantly improved for societal risk classification.

Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis:A population-based study

BACKGROUND The presence of liver metastasis(LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer(NSCLC) patients.The median overall survival of patients with involvement of the liver is less than 5 mo.At present,identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM(NSCLC-LM) are highly desirable.AIM To build a forecasting model to predict the survival time of NSCLC-LM patients.METHODS Data on NSCLC-LM patients were collected from the Surveillance,Epidemiology,and End Results database between 2010 and 2018.Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM.Kaplan-Meier curves were constructed to assess survival time.Cox regression was applied to select the independent prognostic predictors of cancer-specific survival(CSS).A nomogram was established and its prognostic performance was evaluated.RESULTS The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010to 25.2 in 2013,and then declined to 22.1 in 2018.According to the multivariable Cox regression analysis of the training set,age,marital status,sex,race,histological type,T stage,metastatic pattern,and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS(P < 0.05) and were further used to construct a nomogram.The C-indices of the training and validation sets were 0.726 and 0.722,respectively.The results of decision curve analyses(DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility.CONCLUSION We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients.

Quantitative Estimation of Pipeline Slope Disaster Risk in China

China’s economic development is closely related to oil and gas resources,and the country is investing heavily in pipeline construction.Slope geological hazards seriously affect the long-term safe operation of buried pipelines,usually causing pipeline leakage,property and environmental losses,and adverse social impacts.To ensure the safety of pipelines and reduce the probability of pipeline disasters,it is necessary to predict and quantitatively evaluate slope hazards.While there has been much research focus in recent years on the evaluation of pipeline slope disasters and the stress calculation of pipelines under hazards,existing methods only provide information on the occurrence probability of slope events,not whether a slope disaster will lead to pipeline damage.Taking the 2015 Xinzhan landslide in Guizhou Province,China,as an example,this study used discrete elements to simulate landslide events and determine the risk level and scope for pipeline damage,and then established a pipe-soil coupling model to quantitatively evaluate the impact of landslide hazards for pipelines in medium-and high-risk areas.The results provide a reference for future pipeline disaster prevention and control.

Software Analytics of Open Source Business Software

This paper applies software analytics to open source code. Open-source software gives both individuals and businesses the flexibility to work with different parts of available code to modify it or incorporate it into their own project. The open source software market is growing. Major companies such as AWS, Facebook, Google, IBM, Microsoft, Netflix, SAP, Cisco, Intel, and Tesla have joined the open source software community. In this study, a sample of 40 open source applications was selected. Traditional McCabe software metrics including cyclomatic and essential complexities were examined. An analytical comparison of this set of metrics and derived metrics for high risk software was utilized as a basis for addressing risk management in the adoption and integration decisions of open source software. From this comparison, refinements were added, and contemporary concepts of design and data metrics derived from cyclomatic complexity were integrated into a classification scheme for software quality. It was found that 84% of the sample open source applications were classified as moderate low risk or low risk indicating that open source software exhibits low risk characteristics. The 40 open source applications were the base data for the model resulting in a technique which is applicable to any open source code regardless of functionality, language, or size.

On the Issue of Commercial Insurance and Commercial Insurance Market in the Slovak Republic

The article is concentrated on the Slovak commercial insurance, commercial insurance market, non-life insurance, and international risks on the Slovak Republic. Since 1 May 2004, the Slovak insurance market has been part of the uniform European Union insurance market, which includes over 5,000 insurance companies. After Slovakia’s admission to the European Union, several legislative changes have been adopted in the area of commercial insurance industry, which also influenced non-life insurance and the insurance of international risks as part of non-life risks. The most recent act in the area of commercial insurance mentioned in the paper is the Act of the National Council SR No. 39/2015 Coll. on Insurance, in which there are legislative changes in life and also non-life insurance. Basic terms are defined and commented on in the first two chapters （Lowry, Rawlings, ＆ Merkin, 2015）. The nature of international risks as part of non-life risks is described in the second chapter. International risks are classified in the third chapter; international risks are subdivided in the paper into commercial or trade risks, political and economic risks, and special types of risks.

Pancreatic cystic neoplasms:current and future approaches to identify patients at risk

Pancreatic cystic neoplasms(PCNs)are a group of entities with distinct risks and various treatments.Identification of the PCN patients at risk is thus critical.A correct diagnosis is the key to select high-risk patients.However,the misdiagnosis rate is extremely high even computer tomography,magnetic resonance imaging,and endoscopic ultrasonography were applied.Current approaches for differential diagnosis and identifying high-risk patients in certain types of PCNs are not powerful enough to make a clinical acceptable accuracy of diagnosis.The approaches mainly rely on imaging and tumor marker test.We here summarized the current approaches,and reviewed novel approaches under development.For instance,cyst fluid test of glucose or vascular endothelial growth factor A shows the best performance in identifying mucinous cystic neoplasms or serous cystic neoplasms.Multidisciplinary team(MDT)discussion is another way to improve the accuracy of diagnosis.Combination of MDT with validated novel approaches with high sensitivity and specificity is the best way to select truly high-risk patients with PCNs.

Association between change of health care providers and pregnancy exposure to FDA category C, D and X drugs

Background Changing health care providers frequently breaks the continuity of care,which is associated with many health care problems.The purpose of this study was to examine the association between a change of health care providers and pregnancy exposure to FDA category C,D and X drugs.Methods A 50% random sample of women who gave a birth in Saskatchewan between January 1,1997 and December 31,2000 were chosen for this study.The association between the number of changes in health care providers and with pregnancy exposure to category C,D,and X drugs for those women with and without chronic diseases were evaluated using multiple logistical regression,with adjusted odds ratios （ORs） and its 95% confidence intervals （C/s） as the association measures.Results A total of 18 568 women were included in this study.Rates of FDA C,D,and X drug uses were 14.35%,17.07%,21.72%,and 31.14%,in women with no change of provider,1-2 changes,3-5 changes,and more than 5 changes of health care providers.An association between the number of changes of health care providers and pregnancy exposure to FDA C,D,and X drugs existed in women without chronic diseases but not in women with chronic disease.Conclusion Change of health care providers is associated with pregnancy exposure to FDA category C,D and X drugs in women without chronic diseases.

Latest Advancement of Non ST-segment Elevation Acute Coronary Syndrome

Further understanding of the pathphophisyology, advance of the diagnosis instrument and renovation of the risk delamination standard can offer better therapy evidence for the non-ST-segment elevation acute coronary syndrome(NSTE-ACS). Drugs, such as trigeminy antiplatelet drug, prasugrel, fondaparinux and bivalirudin, have brought great clinical effect to the high risk patients. Since the result of the ICTUS test announced and the drug eluting balloon developed, we have reached the newest recognition of how to select a chance for intervention and how to prevent and cure the restenosis of in-stent.