As the global population ages,the incidence of cancer among older adults is increasing.The management of older patients with cancer poses unique challenges due to the age-related physiological changes,multiple comorbi...As the global population ages,the incidence of cancer among older adults is increasing.The management of older patients with cancer poses unique challenges due to the age-related physiological changes,multiple comorbidities,and functional decline often observed in this population.Comprehensive Geriatric Assessment(CGA)has emerged as a valuable tool in oncology to evaluate the overall health and functional status of older cancer patients in order to optimise cancer care for older adults.This comprehensive approach acknowledges the unique challenges faced by elderly patients with cancer and seeks to optimize outcomes by considering their specific circumstances and individual requirements.展开更多
Gastroesophageal reflux disease(GERD) is a very common disorder with increasing prevalence. It is estimated that up to 20%-25% of Americans experience symptoms of GERD weekly. Excessive reflux of acidic often with alk...Gastroesophageal reflux disease(GERD) is a very common disorder with increasing prevalence. It is estimated that up to 20%-25% of Americans experience symptoms of GERD weekly. Excessive reflux of acidic often with alkaline bile salt gastric and duodenal contents results in a multitude of symptoms for the patient including heartburn, regurgitation, cough, and dysphagia. There are also associated complications of GERD including erosive esophagitis, Barrett's esophagus, stricture and adenocarcinoma of the esophagus. While first line treatments for GERD involve mainly lifestyle and non-surgical therapies, surgical interventions have proven to be effective in appropriate circumstances. Anti-reflux operations are aimed at creating an effective barrier to reflux at the gastroesophageal junction and thus attempt to improve physiologic and mechanical issues that may be involved in the pathogenesis of GERD. The decision for surgical intervention in the treatment of GERD, moreover, requires an objective confirmation of the diagnosis. Confirmation is achieved using various preoperative evaluations including: ambulatory p H monitoring, esophageal manometry, upper endoscopy(esophagogastroduodenoscopy) and barium swallow. Upon confirmation of the diagnosis and with appropriate patient criteria met, an antireflux operation is a good alternative to prolonged medical therapy. Currently, minimally invasive gastroesophageal fundoplication is the gold standard for surgical intervention of GERD. Our review outlines the many factors that are involved in surgical decisionmaking. We will review the prominent features that reflect appropriate anti-reflux surgery and present suggestions that are pertinent to surgical practices, based on evidence-based studies.展开更多
With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identify...With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identifying the big data analytics (BDA) attributes. These attributes were classified into four groups (i.e., value innovation, social impact, precision, and completeness of BDA quality) and were found to influence the decision-making performance and business performance outcomes. A structural equation modeling analysis using 382 responses from a BDA related to practitioners indicated that the attributes of representativeness, predictability, interpretability, and innovativeness as related to value innovation greatly enhanced the decision-making confidence and effectiveness of decision makers who make decisions using big data. In addition, individuality, collectivity, and willfulness, which are related to social impact, also greatly improved the decision-making confidence and effectiveness of the same decision makers. This shows that the value innovation and social impact, which have received relatively less attention in previous studies, are the crucial attributes for BDA quality as they influence the decision-making performance. Comprehensiveness, factuality, and realism, which are linked to completeness, also have similar results. Furthermore, the higher the decision-making confidence of the decision makers who used big data was, the higher the financial performance of their companies. In addition, high decision-making confidence using big data was found to improve the nonfinancial performance metrics such as customer satisfaction and quality levels as well as product development capabilities. High decision-making effectiveness with big data was also shown to improve the nonfinancial performance metrics.展开更多
Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs...Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.展开更多
In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite...In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite due to the increasing return of invest-ment.Hence,it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending.Accordingly,this study aims to analyze a unique risk set and the stra-tegic priorities of fintech lending for clean energy projects.The most important contri-butions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets.The extension of multi stepwise weight assessment ratio analysis(M-SWARA)is applied for weighting the risk factors of fintech lending.The extension of elimination and choice translating reality(ELECTRE)is employed for con-structing and ranking the risk-based strategic priorities for clean energy projects.In this process,data is obtained with the evaluation of three different decision makers.The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA.Hence,the causality analysis between the criteria can also be performed in this proposed model.The find-ings demonstrate that security is the most critical risk factor for fintech lending system.Moreover,volume is found as the most critical risk-based strategy for fintech lending.In this context,fintech companies need to take some precautions to effectively manage the security risk.For this purpose,the main risks to information technologies need to be clearly identified.Next,control steps should be put for these risk展开更多
Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection.Despite,new automated...Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection.Despite,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray imaging.Thoracic imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines.Through this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected patients.This model is trained on a dataset containing thousands of X-ray images collected from different sources.The model was tested and evaluated on an independent dataset.In order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning technique.This experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with pneumonia.This proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging goal.The finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.展开更多
文摘As the global population ages,the incidence of cancer among older adults is increasing.The management of older patients with cancer poses unique challenges due to the age-related physiological changes,multiple comorbidities,and functional decline often observed in this population.Comprehensive Geriatric Assessment(CGA)has emerged as a valuable tool in oncology to evaluate the overall health and functional status of older cancer patients in order to optimise cancer care for older adults.This comprehensive approach acknowledges the unique challenges faced by elderly patients with cancer and seeks to optimize outcomes by considering their specific circumstances and individual requirements.
文摘Gastroesophageal reflux disease(GERD) is a very common disorder with increasing prevalence. It is estimated that up to 20%-25% of Americans experience symptoms of GERD weekly. Excessive reflux of acidic often with alkaline bile salt gastric and duodenal contents results in a multitude of symptoms for the patient including heartburn, regurgitation, cough, and dysphagia. There are also associated complications of GERD including erosive esophagitis, Barrett's esophagus, stricture and adenocarcinoma of the esophagus. While first line treatments for GERD involve mainly lifestyle and non-surgical therapies, surgical interventions have proven to be effective in appropriate circumstances. Anti-reflux operations are aimed at creating an effective barrier to reflux at the gastroesophageal junction and thus attempt to improve physiologic and mechanical issues that may be involved in the pathogenesis of GERD. The decision for surgical intervention in the treatment of GERD, moreover, requires an objective confirmation of the diagnosis. Confirmation is achieved using various preoperative evaluations including: ambulatory p H monitoring, esophageal manometry, upper endoscopy(esophagogastroduodenoscopy) and barium swallow. Upon confirmation of the diagnosis and with appropriate patient criteria met, an antireflux operation is a good alternative to prolonged medical therapy. Currently, minimally invasive gastroesophageal fundoplication is the gold standard for surgical intervention of GERD. Our review outlines the many factors that are involved in surgical decisionmaking. We will review the prominent features that reflect appropriate anti-reflux surgery and present suggestions that are pertinent to surgical practices, based on evidence-based studies.
文摘With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identifying the big data analytics (BDA) attributes. These attributes were classified into four groups (i.e., value innovation, social impact, precision, and completeness of BDA quality) and were found to influence the decision-making performance and business performance outcomes. A structural equation modeling analysis using 382 responses from a BDA related to practitioners indicated that the attributes of representativeness, predictability, interpretability, and innovativeness as related to value innovation greatly enhanced the decision-making confidence and effectiveness of decision makers who make decisions using big data. In addition, individuality, collectivity, and willfulness, which are related to social impact, also greatly improved the decision-making confidence and effectiveness of the same decision makers. This shows that the value innovation and social impact, which have received relatively less attention in previous studies, are the crucial attributes for BDA quality as they influence the decision-making performance. Comprehensiveness, factuality, and realism, which are linked to completeness, also have similar results. Furthermore, the higher the decision-making confidence of the decision makers who used big data was, the higher the financial performance of their companies. In addition, high decision-making confidence using big data was found to improve the nonfinancial performance metrics such as customer satisfaction and quality levels as well as product development capabilities. High decision-making effectiveness with big data was also shown to improve the nonfinancial performance metrics.
基金supported by National Social Science Foundation of China (Grant No.17ZDA030).
文摘Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.
基金was the Key Scientific Research Project of Colleges and Universities in Henan Province“Research on the key role of Investment in the Optimization and upgrading of Industrial structure in Henan Province”(22A790014)National scientific research project cultivation fund project"Research on the Endogenous Mechanism,Performance Evaluation and Optimization Path of Science and Technology Finance Boosting China’s High quality Economic Development"(XKPY-2022030).
文摘In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite due to the increasing return of invest-ment.Hence,it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending.Accordingly,this study aims to analyze a unique risk set and the stra-tegic priorities of fintech lending for clean energy projects.The most important contri-butions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets.The extension of multi stepwise weight assessment ratio analysis(M-SWARA)is applied for weighting the risk factors of fintech lending.The extension of elimination and choice translating reality(ELECTRE)is employed for con-structing and ranking the risk-based strategic priorities for clean energy projects.In this process,data is obtained with the evaluation of three different decision makers.The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA.Hence,the causality analysis between the criteria can also be performed in this proposed model.The find-ings demonstrate that security is the most critical risk factor for fintech lending system.Moreover,volume is found as the most critical risk-based strategy for fintech lending.In this context,fintech companies need to take some precautions to effectively manage the security risk.For this purpose,the main risks to information technologies need to be clearly identified.Next,control steps should be put for these risk
基金This research is funded by the Deanship of Scientific Research at King Khalid University through Large Groups.(Project under grant number(RGP.2/111/43)).
文摘Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection.Despite,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray imaging.Thoracic imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines.Through this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected patients.This model is trained on a dataset containing thousands of X-ray images collected from different sources.The model was tested and evaluated on an independent dataset.In order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning technique.This experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with pneumonia.This proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging goal.The finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.
