Default Probabilities quantitatively measures the credit risk that a borrower will be unable or unwilling to repay its debt. An accurate model to estimate, as a function of time, these default probabilities is of cruc...Default Probabilities quantitatively measures the credit risk that a borrower will be unable or unwilling to repay its debt. An accurate model to estimate, as a function of time, these default probabilities is of crucial importance in the credit derivatives market. In this work, we adapt Merton’s [1] original works on credit risk, consumption and portfolio rules to model an individual wealth scenario, and apply it to compute this individual default probabilities. Using our model, we also compute the time depending individual default intensities, recovery rates, hazard rate and risk premiums. Hence, as a straight-forward application, our model can be used as novel way to measure the credit risk of individuals.展开更多
BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strate...BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC.However,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular characteristics.The most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver variability.AIM To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue.METHODS This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors.RESULTS The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables.The model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical utility.CONCLUSION The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC.This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables,demonstrating superior performance and clinical applicability compared to existing models.The study provides new insights into the potential of deep learning to extract valuable information from tumor histology,in turn,improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.展开更多
While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, i...While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, in gastric cancer mortality peaks in thefirst two years of follow-up and declines thereafter.Also several risk factors, such as TNM stage, largelyaffect mortality in the first years after surgery, whileafterward their effect tends to fade. Temporal trendsin mortality were compared between a gastric cancerseries and a cohort of type 2 diabetic patients. Forthis purpose, 937 patients, undergoing curativegastrectomy with D1/D2/D3 lymphadenectomy forgastric cancer in three GIRCG (Gruppo Italiano RicercaCancro Gastrico = Italian Research Group for GastricCancer) centers, were compared with 7148 type 2diabetic patients from the Verona Diabetes Study. Inthe early/advanced gastric cancer series, mortality fromrecurrence peaked to 200 deaths per 1000 personyears1 year after gastrectomy and then declined,becoming lower than 40 deaths per 1000 person-yearsafter 5 years and lower than 20 deaths after 8 years.Mortality peak occurred earlier in more advanced Tand N tiers. At variance, in the Verona diabetic cohort overall mortality slowly increased during a 10-yearfollow-up, with ageing of the type 2 diabetic patients.Seasonal oscillations were also recorded, mortalitybeing higher during winter than during summer. Alsothe most important prognostic factors presented adifferent temporal pattern in the two diseases: whilethe prognostic significance of T and N stage markedlydecrease over time, differences in survival amongpatients treated with diet, oral hypoglycemic drugsor insulin were consistent throughout the follow-up.Time variations in prognostic significance of main riskfactors, their impact on survival analysis and possiblesolutions were evaluated in another GIRCG series of568 patients with advanced gastric cancer, undergoingcurative gastrectomy with D2/D3 lymphadenectomy.Survival curves in the two different histotypes (intestinaland mixed/diffuse) were superimposed in the first threeyears of follow-up and diverged thereafter. Likewise,survival curves as a function of site (fundus vs body/antrum) started to diverge after the first year. On thecontrary, survival curves differed among age classesfrom the very beginning, due to different post-operativemortality, which increased from 0.5% in patients aged65-74 years to 9.9% in patients aged 75-91 years;this discrepancy later disappeared. Accordingly, theproportional hazards assumption of the Cox modelwas violated, as regards age, site and histology. Tocope with this problem, multivariable survival analysiswas performed by separately considering either thefirst two years of follow-up or subsequent years.Histology and site were significant predictors only aftertwo years, while T and N, although significant bothin the short-term and in the long-term, became lessimportant in the second part of follow-up. Increasingage was associated with higher mortality in the firsttwo years, but not thereafter. Splitting survival timewhen performing survival analysis allows to distinguishbetween short-term and long-term risk factors.Alternative statistical solutions could be to excludepost-operative mortality, to introduce in the modeltime-dependent covariates or to stratify on variablesviolating proportionality assumption.展开更多
Background:Linezolid-associated thrombocytopenia(LAT)leads to drug withdrawal associated with a poor prognosis.Some risk factors for LAT have been identified;however,the sample size of previous studies was small,data ...Background:Linezolid-associated thrombocytopenia(LAT)leads to drug withdrawal associated with a poor prognosis.Some risk factors for LAT have been identified;however,the sample size of previous studies was small,data from elderly individuals are limited,and a simple risk score scale was not established to predict LAT at anearly stage,making it difficult to identify and intervene in LAT at an early stage.Methods:In this single-center retrospective case-control study,we enrolled elderly patients treated with linezolidin the intensive care unit from January 2015 to December 2020.All the data of enrolled patients,includingdemographic information and laboratory findings at baseline,were collected.We analyzed the incidence andrisk factors for LAT and established a nomogram risk prediction model for LAT in the elderly population.Results:A total of 428 elderly patients were enrolled,and the incidence of LAT was 35.5%(152/428).Age≥80 years old(OR=1.980;95%CI:1.179–3.325;P=0.010),duration of linezolid≥10 days(OR=1.100;95%CI:1.050–1.152;P<0.0001),platelet count at baseline(100–149×10^(9)/L vs.≥200×10^(9)/L,OR=8.205,95%CI:4.419–15.232,P<0.0001;150–199×10^(9)/L vs.≥200×10^(9)/L,OR=3.067,95%CI:1.676–5.612,P<0.001),leukocytecount at baseline≥16×10^(9)/L(OR=2.580;95%CI:1.523–4.373;P<0.0001),creatinine clearance<50 mL/min(OR=2.323;95%CI:1.388–3.890;P=0.001),and total protein<60 g/L(OR=1.741;95%CI:1.039–2.919;P=0.035)were associated with LAT.The nomogram prediction model called“ADPLCP”(age,duration,platelet,leukocyte,creatinine clearance,protein)was established based on logistic regression.The area under the curve(AUC)of ADPLCP was 0.802(95%CI:0.748–0.856;P<0.0001),with 78.9%sensitivity and 69.2%specificity(cut-off was 108).Risk stratification for LAT was performed based on“ADPLCP.”Total points of<100 were defined as low risk,and the possibility of LAT was<32.0%.Total points of 100–150 were defined as medium risk,and the possibility of LAT was 32.0–67.5%.A total point>150 was defined as high risk,and the probability ofLAT was>67.5%.Conclusions:We created the ADPLCP risk score scale to predict the occurrence of LAT in elderly individuals.ADPLCP is simple and feasible and is helpful for the early determination of LAT to guide drug withdrawal orearly intervention.展开更多
The degradation data of multi-components in missile is derived by periodical testing. How to use these data to assess the storage reliability (SR) of the whole missile is a difficult problem in current research. An SR...The degradation data of multi-components in missile is derived by periodical testing. How to use these data to assess the storage reliability (SR) of the whole missile is a difficult problem in current research. An SR assessment model based on competition failure of multi-components in missile is proposed. By analyzing the missile life profile and its storage failure feature, the key components in missile are obtained and the characteristics voltage is assumed to be its key performance parameter. When the voltage testing data of key components in missile are available, a state space model (SSM) is applied to obtain the whole missile degradation state, which is defined as the missile degradation degree (DD). A Wiener process with the time-scale model (TSM) is applied to build the degradation failure model with individual variability and nonlinearity. The Weibull distribution and proportional risk model are applied to build an outburst failure model with performance degradation effect. Furthermore, a competition failure model with the correlation between degradation failure and outburst failure is proposed. A numerical example with a set of missiles in storage is analyzed to demonstrate the accuracy and superiority of the proposed model.展开更多
In the actuarial literature, several exact and approximative recursive methods have been proposed for calculating the distribution of a sum of mutually independent compound Bernoulli distributed random variables. In t...In the actuarial literature, several exact and approximative recursive methods have been proposed for calculating the distribution of a sum of mutually independent compound Bernoulli distributed random variables. In this paper, we give an overview of these methods. We compare their performance with the straight- forward convolution technique by counting the number of dot operations involved in each method. It turns out that in many practicle situations, the recursive methods outperform the convolution method.展开更多
In this paper, we propose a customer-based individual risk model, in which potential claims by customers are described as i.i.d, heavy-tailed random variables, but different insurance policy holders are allowed to hav...In this paper, we propose a customer-based individual risk model, in which potential claims by customers are described as i.i.d, heavy-tailed random variables, but different insurance policy holders are allowed to have different probabilities to make actual claims. Some precise large deviation results for the prospectiveoss process are derived under certain mild assumptions, with emphasis on the case of heavy-tailed distribution function class ERV (extended regular variation). Lundberg type limiting results on the finite time ruin probabilities are also investigated.展开更多
For stochastic loss reserving,we propose an individual information model(IIM)which accom-modates not only individual/micro data consisting of incurring times,reporting developments,settlement developments as well as p...For stochastic loss reserving,we propose an individual information model(IIM)which accom-modates not only individual/micro data consisting of incurring times,reporting developments,settlement developments as well as payments of individual claims but also heterogeneity among policies.We give over-dispersed Poisson assumption about the moments of reporting developments and payments of every individual claims.Model estimation is conducted under quasi-likelihood theory.Analytic expressions are derived for the expectation and variance of outstanding liabilities,given historical observations.We utilise conditional mean square error of prediction(MSEP)to measure the accuracy of loss reserving and also theoretically prove that when risk portfolio size is large enough,IIM shows a higher prediction accuracy than individ-ual/micro data model(IDM)in predicting the outstanding liabilities,if the heterogeneity indeed influences claims developments and otherwise IIM is asymptotically equivalent to IDM.Some simulations are conducted to investigate the conditional MSEPs for IIM and IDM.A real data analysis is performed basing on real observations in health insurance.展开更多
基于液氯储运过程中的安全现状分析和事故统计,结合挪威船级社的定量风险分析软件SAFETI(Software forAssessment of Flammable,Explosive and Toxic Impacts),分析了氯气的危险特性以及液氯储运过程中因泄漏而导致的毒害危险性,归纳出...基于液氯储运过程中的安全现状分析和事故统计,结合挪威船级社的定量风险分析软件SAFETI(Software forAssessment of Flammable,Explosive and Toxic Impacts),分析了氯气的危险特性以及液氯储运过程中因泄漏而导致的毒害危险性,归纳出了液氯储运过程中可能发生的各种泄漏事故类型;并运用SAFETI软件对某液氯槽车发生泄漏后的毒性危害后果及风险进行定量评价,建立具针对性的评价模型,模拟预测事故后果及风险,取得了液氯泄漏毒害事故危害程度和范围及造成的个人风险和社会风险的计算机模拟图表及报告等,对预测、预防液氯泄漏毒害事故以及减少事故造成的人员伤亡和财产损失具有工程应用价值.展开更多
文摘Default Probabilities quantitatively measures the credit risk that a borrower will be unable or unwilling to repay its debt. An accurate model to estimate, as a function of time, these default probabilities is of crucial importance in the credit derivatives market. In this work, we adapt Merton’s [1] original works on credit risk, consumption and portfolio rules to model an individual wealth scenario, and apply it to compute this individual default probabilities. Using our model, we also compute the time depending individual default intensities, recovery rates, hazard rate and risk premiums. Hence, as a straight-forward application, our model can be used as novel way to measure the credit risk of individuals.
文摘BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC.However,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular characteristics.The most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver variability.AIM To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue.METHODS This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors.RESULTS The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables.The model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical utility.CONCLUSION The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC.This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables,demonstrating superior performance and clinical applicability compared to existing models.The study provides new insights into the potential of deep learning to extract valuable information from tumor histology,in turn,improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.
文摘While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, in gastric cancer mortality peaks in thefirst two years of follow-up and declines thereafter.Also several risk factors, such as TNM stage, largelyaffect mortality in the first years after surgery, whileafterward their effect tends to fade. Temporal trendsin mortality were compared between a gastric cancerseries and a cohort of type 2 diabetic patients. Forthis purpose, 937 patients, undergoing curativegastrectomy with D1/D2/D3 lymphadenectomy forgastric cancer in three GIRCG (Gruppo Italiano RicercaCancro Gastrico = Italian Research Group for GastricCancer) centers, were compared with 7148 type 2diabetic patients from the Verona Diabetes Study. Inthe early/advanced gastric cancer series, mortality fromrecurrence peaked to 200 deaths per 1000 personyears1 year after gastrectomy and then declined,becoming lower than 40 deaths per 1000 person-yearsafter 5 years and lower than 20 deaths after 8 years.Mortality peak occurred earlier in more advanced Tand N tiers. At variance, in the Verona diabetic cohort overall mortality slowly increased during a 10-yearfollow-up, with ageing of the type 2 diabetic patients.Seasonal oscillations were also recorded, mortalitybeing higher during winter than during summer. Alsothe most important prognostic factors presented adifferent temporal pattern in the two diseases: whilethe prognostic significance of T and N stage markedlydecrease over time, differences in survival amongpatients treated with diet, oral hypoglycemic drugsor insulin were consistent throughout the follow-up.Time variations in prognostic significance of main riskfactors, their impact on survival analysis and possiblesolutions were evaluated in another GIRCG series of568 patients with advanced gastric cancer, undergoingcurative gastrectomy with D2/D3 lymphadenectomy.Survival curves in the two different histotypes (intestinaland mixed/diffuse) were superimposed in the first threeyears of follow-up and diverged thereafter. Likewise,survival curves as a function of site (fundus vs body/antrum) started to diverge after the first year. On thecontrary, survival curves differed among age classesfrom the very beginning, due to different post-operativemortality, which increased from 0.5% in patients aged65-74 years to 9.9% in patients aged 75-91 years;this discrepancy later disappeared. Accordingly, theproportional hazards assumption of the Cox modelwas violated, as regards age, site and histology. Tocope with this problem, multivariable survival analysiswas performed by separately considering either thefirst two years of follow-up or subsequent years.Histology and site were significant predictors only aftertwo years, while T and N, although significant bothin the short-term and in the long-term, became lessimportant in the second part of follow-up. Increasingage was associated with higher mortality in the firsttwo years, but not thereafter. Splitting survival timewhen performing survival analysis allows to distinguishbetween short-term and long-term risk factors.Alternative statistical solutions could be to excludepost-operative mortality, to introduce in the modeltime-dependent covariates or to stratify on variablesviolating proportionality assumption.
文摘Background:Linezolid-associated thrombocytopenia(LAT)leads to drug withdrawal associated with a poor prognosis.Some risk factors for LAT have been identified;however,the sample size of previous studies was small,data from elderly individuals are limited,and a simple risk score scale was not established to predict LAT at anearly stage,making it difficult to identify and intervene in LAT at an early stage.Methods:In this single-center retrospective case-control study,we enrolled elderly patients treated with linezolidin the intensive care unit from January 2015 to December 2020.All the data of enrolled patients,includingdemographic information and laboratory findings at baseline,were collected.We analyzed the incidence andrisk factors for LAT and established a nomogram risk prediction model for LAT in the elderly population.Results:A total of 428 elderly patients were enrolled,and the incidence of LAT was 35.5%(152/428).Age≥80 years old(OR=1.980;95%CI:1.179–3.325;P=0.010),duration of linezolid≥10 days(OR=1.100;95%CI:1.050–1.152;P<0.0001),platelet count at baseline(100–149×10^(9)/L vs.≥200×10^(9)/L,OR=8.205,95%CI:4.419–15.232,P<0.0001;150–199×10^(9)/L vs.≥200×10^(9)/L,OR=3.067,95%CI:1.676–5.612,P<0.001),leukocytecount at baseline≥16×10^(9)/L(OR=2.580;95%CI:1.523–4.373;P<0.0001),creatinine clearance<50 mL/min(OR=2.323;95%CI:1.388–3.890;P=0.001),and total protein<60 g/L(OR=1.741;95%CI:1.039–2.919;P=0.035)were associated with LAT.The nomogram prediction model called“ADPLCP”(age,duration,platelet,leukocyte,creatinine clearance,protein)was established based on logistic regression.The area under the curve(AUC)of ADPLCP was 0.802(95%CI:0.748–0.856;P<0.0001),with 78.9%sensitivity and 69.2%specificity(cut-off was 108).Risk stratification for LAT was performed based on“ADPLCP.”Total points of<100 were defined as low risk,and the possibility of LAT was<32.0%.Total points of 100–150 were defined as medium risk,and the possibility of LAT was 32.0–67.5%.A total point>150 was defined as high risk,and the probability ofLAT was>67.5%.Conclusions:We created the ADPLCP risk score scale to predict the occurrence of LAT in elderly individuals.ADPLCP is simple and feasible and is helpful for the early determination of LAT to guide drug withdrawal orearly intervention.
基金supported by the National Defense Foundation of China(71601183)
文摘The degradation data of multi-components in missile is derived by periodical testing. How to use these data to assess the storage reliability (SR) of the whole missile is a difficult problem in current research. An SR assessment model based on competition failure of multi-components in missile is proposed. By analyzing the missile life profile and its storage failure feature, the key components in missile are obtained and the characteristics voltage is assumed to be its key performance parameter. When the voltage testing data of key components in missile are available, a state space model (SSM) is applied to obtain the whole missile degradation state, which is defined as the missile degradation degree (DD). A Wiener process with the time-scale model (TSM) is applied to build the degradation failure model with individual variability and nonlinearity. The Weibull distribution and proportional risk model are applied to build an outburst failure model with performance degradation effect. Furthermore, a competition failure model with the correlation between degradation failure and outburst failure is proposed. A numerical example with a set of missiles in storage is analyzed to demonstrate the accuracy and superiority of the proposed model.
基金Support by the Onderzoeksfonds K.U.Leuven(GOA/02:Actuarile,financile en statistische aspecten van afhankelijkheden in vcrzekerings-en financile portefeuilles)Support by the Dutch Organization for Scientific Research(No.NWO 048.031.2003.001)
文摘In the actuarial literature, several exact and approximative recursive methods have been proposed for calculating the distribution of a sum of mutually independent compound Bernoulli distributed random variables. In this paper, we give an overview of these methods. We compare their performance with the straight- forward convolution technique by counting the number of dot operations involved in each method. It turns out that in many practicle situations, the recursive methods outperform the convolution method.
基金Supported by the National Natural Science Foundation of China(No.10971157)
文摘In this paper, we propose a customer-based individual risk model, in which potential claims by customers are described as i.i.d, heavy-tailed random variables, but different insurance policy holders are allowed to have different probabilities to make actual claims. Some precise large deviation results for the prospectiveoss process are derived under certain mild assumptions, with emphasis on the case of heavy-tailed distribution function class ERV (extended regular variation). Lundberg type limiting results on the finite time ruin probabilities are also investigated.
基金This work was supported by the Natural Science Foundation of China(71771089)the Shanghai Philosophy and Social Sci-ence Foundation(2015BGL001)+1 种基金the National Social Science Foundation Key Program of China(17ZDA091)China Scholarship Council(201906140045)。
文摘For stochastic loss reserving,we propose an individual information model(IIM)which accom-modates not only individual/micro data consisting of incurring times,reporting developments,settlement developments as well as payments of individual claims but also heterogeneity among policies.We give over-dispersed Poisson assumption about the moments of reporting developments and payments of every individual claims.Model estimation is conducted under quasi-likelihood theory.Analytic expressions are derived for the expectation and variance of outstanding liabilities,given historical observations.We utilise conditional mean square error of prediction(MSEP)to measure the accuracy of loss reserving and also theoretically prove that when risk portfolio size is large enough,IIM shows a higher prediction accuracy than individ-ual/micro data model(IDM)in predicting the outstanding liabilities,if the heterogeneity indeed influences claims developments and otherwise IIM is asymptotically equivalent to IDM.Some simulations are conducted to investigate the conditional MSEPs for IIM and IDM.A real data analysis is performed basing on real observations in health insurance.
文摘基于液氯储运过程中的安全现状分析和事故统计,结合挪威船级社的定量风险分析软件SAFETI(Software forAssessment of Flammable,Explosive and Toxic Impacts),分析了氯气的危险特性以及液氯储运过程中因泄漏而导致的毒害危险性,归纳出了液氯储运过程中可能发生的各种泄漏事故类型;并运用SAFETI软件对某液氯槽车发生泄漏后的毒性危害后果及风险进行定量评价,建立具针对性的评价模型,模拟预测事故后果及风险,取得了液氯泄漏毒害事故危害程度和范围及造成的个人风险和社会风险的计算机模拟图表及报告等,对预测、预防液氯泄漏毒害事故以及减少事故造成的人员伤亡和财产损失具有工程应用价值.