AIM:To analysis of research hotspots and trends on the application of premium intraocular lens(PIOLs)in the past 2 decades.METHODS:The literature search was performed on the Web of Science and included PIOLs studies p...AIM:To analysis of research hotspots and trends on the application of premium intraocular lens(PIOLs)in the past 2 decades.METHODS:The literature search was performed on the Web of Science and included PIOLs studies published between January 2000 and December 2022.The retrieved literature was collated and analyzed by R-tool’s Bibliometrix package,CitNetExplorer,CiteSpace and other software.RESULTS:A total of 1801 articles about PIOLs were obtained,most of which were published in Spain and the United States.The organization that published the most articles was the University of Valencia in Spain.Alió JL,and Montés-Micó R,from Spain were the most influential authors in this field.The Journal of Cataract and Refractive Surgery and Journal of Refractive Surgery were the core journals for this field;the top 10 cited articles mainly focus on postoperative satisfaction with multifocal intraocular lens(IOLs)and postoperative results of toric IOLs.Through the keyword analysis,we found that trifocal IOLs,astigmatism and extended depth of focus(EDoF)IOLs are the most discussed topics at present,and the importance of astigmatism and the clinical application of the new generation of PIOLs are the emerging research trends.CONCLUSION:Bibliometric analysis can effectively help to identify multilevel concerns in PIOLs research and the prevailing research trends in the realm of PIOLs encompass the adoption of EDoF IOLs,trifocal IOLs,and their respective Toric models.展开更多
Reinsurance is an effective risk management tool for insurers to stabilize their profitability. In a typical reinsurance treaty, an insurer cedes part of the loss to a reinsurer. As the insurer faces an increasing num...Reinsurance is an effective risk management tool for insurers to stabilize their profitability. In a typical reinsurance treaty, an insurer cedes part of the loss to a reinsurer. As the insurer faces an increasing number of total losses in the insurance market, the insurer might expect the reinsurer to bear an increasing proportion of the total loss, that is the insurer might expect the reinsurer to pay an increasing proportion of the total claim amount when he faces an increasing number of total claims in the insurance market. Motivated by this, we study the optimal reinsurance problem under the Vajda condition. To prevent moral hazard and reflect the spirit of reinsurance, we assume that the retained loss function is increasing and the ceded loss function satisfies the Vajda condition. We derive the explicit expression of the optimal reinsurance under the TVaR risk measure and TVaR premium principle from the perspective of both an insurer and a reinsurer. Our results show that the explicit expression of the optimal reinsurance is in the form of two or three interconnected line segments. Under an additional mild constraint, we get the optimal parameters and find the optimal reinsurance strategy is full reinsurance, no reinsurance, stop loss reinsurance, or quota-share reinsurance. Finally, we gave an example to analyze the impact of the weighting factor on optimal reinsurance.展开更多
Traditional machine learning metrics(TMLMs)are quite useful for the current research work precision,recall,accuracy,MSE and RMSE.Not enough for a practitioner to be confident about the performance and dependability of...Traditional machine learning metrics(TMLMs)are quite useful for the current research work precision,recall,accuracy,MSE and RMSE.Not enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%.We included in the prediction process,machine learning models(MLMs)with greater than 99%accuracy with a sensitivity of 95%–98%and specifically in the database.We need to explain the model to domain specialists through the MLMs.Human-understandable explanations in addition to ML professionals must establish trust in the prediction of our model.This is achieved by creating a model-independent,locally accurate explanation set that makes it better than the primary model.As we know that human interaction with machine learning systems on this model’s interpretability is more crucial.For supporting set validations in model selection insurance premium prediction.In this study,we proposed the use of the(LIME and SHAP)approach to understand research properly and explain a model developed using random forest regression to predict insurance premiums.The SHAP algorithm’s drawback,as seen in our experiments,is its lengthy computing time—to produce the findings,it must compute every possible combination.In addition,the experiments conducted were intended to focus on the model’s interpretability and explain its ability using LIME and SHAP,not the insurance premium charge prediction.Three experiments were conducted through experiment,one was to interpret the random forest regression model using LIME techniques.In experiment 2,we used the SHAP technique to interpret the model insurance premium prediction(IPP).展开更多
基金Supported by the National Natural Science Foundation of China(No.82371033No.81970772)+1 种基金the Tianjin Natural Science Foundation(No.21JCZDJC01250)the Tianjin Key Medical Discipline(Specialty)Construction Project(No.TJYXZDXK-016A).
文摘AIM:To analysis of research hotspots and trends on the application of premium intraocular lens(PIOLs)in the past 2 decades.METHODS:The literature search was performed on the Web of Science and included PIOLs studies published between January 2000 and December 2022.The retrieved literature was collated and analyzed by R-tool’s Bibliometrix package,CitNetExplorer,CiteSpace and other software.RESULTS:A total of 1801 articles about PIOLs were obtained,most of which were published in Spain and the United States.The organization that published the most articles was the University of Valencia in Spain.Alió JL,and Montés-Micó R,from Spain were the most influential authors in this field.The Journal of Cataract and Refractive Surgery and Journal of Refractive Surgery were the core journals for this field;the top 10 cited articles mainly focus on postoperative satisfaction with multifocal intraocular lens(IOLs)and postoperative results of toric IOLs.Through the keyword analysis,we found that trifocal IOLs,astigmatism and extended depth of focus(EDoF)IOLs are the most discussed topics at present,and the importance of astigmatism and the clinical application of the new generation of PIOLs are the emerging research trends.CONCLUSION:Bibliometric analysis can effectively help to identify multilevel concerns in PIOLs research and the prevailing research trends in the realm of PIOLs encompass the adoption of EDoF IOLs,trifocal IOLs,and their respective Toric models.
文摘Reinsurance is an effective risk management tool for insurers to stabilize their profitability. In a typical reinsurance treaty, an insurer cedes part of the loss to a reinsurer. As the insurer faces an increasing number of total losses in the insurance market, the insurer might expect the reinsurer to bear an increasing proportion of the total loss, that is the insurer might expect the reinsurer to pay an increasing proportion of the total claim amount when he faces an increasing number of total claims in the insurance market. Motivated by this, we study the optimal reinsurance problem under the Vajda condition. To prevent moral hazard and reflect the spirit of reinsurance, we assume that the retained loss function is increasing and the ceded loss function satisfies the Vajda condition. We derive the explicit expression of the optimal reinsurance under the TVaR risk measure and TVaR premium principle from the perspective of both an insurer and a reinsurer. Our results show that the explicit expression of the optimal reinsurance is in the form of two or three interconnected line segments. Under an additional mild constraint, we get the optimal parameters and find the optimal reinsurance strategy is full reinsurance, no reinsurance, stop loss reinsurance, or quota-share reinsurance. Finally, we gave an example to analyze the impact of the weighting factor on optimal reinsurance.
文摘Traditional machine learning metrics(TMLMs)are quite useful for the current research work precision,recall,accuracy,MSE and RMSE.Not enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%.We included in the prediction process,machine learning models(MLMs)with greater than 99%accuracy with a sensitivity of 95%–98%and specifically in the database.We need to explain the model to domain specialists through the MLMs.Human-understandable explanations in addition to ML professionals must establish trust in the prediction of our model.This is achieved by creating a model-independent,locally accurate explanation set that makes it better than the primary model.As we know that human interaction with machine learning systems on this model’s interpretability is more crucial.For supporting set validations in model selection insurance premium prediction.In this study,we proposed the use of the(LIME and SHAP)approach to understand research properly and explain a model developed using random forest regression to predict insurance premiums.The SHAP algorithm’s drawback,as seen in our experiments,is its lengthy computing time—to produce the findings,it must compute every possible combination.In addition,the experiments conducted were intended to focus on the model’s interpretability and explain its ability using LIME and SHAP,not the insurance premium charge prediction.Three experiments were conducted through experiment,one was to interpret the random forest regression model using LIME techniques.In experiment 2,we used the SHAP technique to interpret the model insurance premium prediction(IPP).
