Personalized cardiovascular intervention simulation system

Background This study proposes a series of geometry and physics modeling methods for personalized cardiovascular intervention procedures,which can be applied to a virtual endovascular simulator.Methods Based on personalized clinical computed tomography angiography(CTA)data,mesh models of the cardiovascular system were constructed semi-automatically.By coupling 4 D magnetic resonance imaging(MRI)sequences corresponding to a complete cardiac cycle with related physics models,a hybrid kinetic model of the cardiovascular system was built to drive kinematics and dynamics simulation.On that basis,the surgical procedures related to intervention instruments were simulated using specially-designed physics models.These models can be solved in real-time;therefore,the complex interactions between blood vessels and instruments can be well simulated.Additionally,X-ray imaging simulation algorithms and realistic rendering algorithms for virtual intervention scenes are also proposed.In particular,instrument tracking hardware with haptic feedback was developed to serve as the interaction interface of real instruments and the virtual intervention system.Finally,a personalized cardiovascular intervention simulation system was developed by integrating the techniques mentioned above.Results This system supported instant modeling and simulation of personalized clinical data and significantly improved the visual and haptic immersions of vascular intervention simulation.Conclusions It can be used in teaching basic cardiology and effectively satisfying the demands of intervention training,personalized intervention planning,and rehearsing.

Game theory approach to optimal capital cost allocation in pollution control

This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.

Validation of different personalized risk models of chemotherapy-induced nausea and vomiting:results of a randomized,double-blind,phase III trial of fosaprepitant for cancer patients treated with high-dose cisplatin

Background:Highly emetogenic chemotherapy induces emesis in cancer patients without prophylaxis.The purpose of this study was to evaluate the efficacy and safety of a fosaprepitant-based triple antiemetic regimen for the prevention of chemotherapy-induced nausea and vomiting(CINV)in patients with solid malignant tumors,determine risk factors and externally validate different personalized risk models for CINV.Methods:This phase III trial was designed to test the non-inferiority of fosaprepitant toward aprepitant in cancer patients who were to receive the first cycle of single-day cisplatin chemotherapy.The primary endpoint was complete response(CR)during the overall phase(OP)with a non-inferiority margin of 10.0%.Logistic regression modelswere used to assess the risk factors ofCRand no nausea.To validate the personalized risk models,the accuracy of the risk scoring systems was determined by measuring the specificity,sensitivity and area under the receiver operating characteristic(ROC)curve(AUC),while the predictive accuracy of the nomogram was measured using concordance index(C-index).Results:A total of 720 patients were randomly assigned.CR during the OP in the fosaprepitant group was not inferior to that in the aprepitant group(78.1%vs.77.7%,P=0.765)with a between-group difference of 0.4%(95%CI,-5.7%to 6.6%).Female sex,higher cisplatin dose(≥70 mg/m2),no history of drinking and larger body surface area(BSA)were significantly associated with nausea.The AUC for the acute and delayed CINV risk indexes was 0.68(95%CI:0.66-0.71)and 0.66(95%CI:0.61-0.70),respectively,and the C-index for nomogram CINV prediction was 0.59(95%CI,0.54-0.64).Using appropriate cutoff points,the three models could stratify patients with high-or low-risk CINV.No nausea and CR rate were significantly higher in the low-risk group than in the high-risk group(P<0.001).Conclusions:Fosaprepitant-based triple prophylaxis demonstrated non-inferior control for preventing CINV in patients treated with cisplatin-base chemotherapy.Female cancer patients without a history of alcohol consumption,with larger BSA and received high-dose cisplatin might be more vulnerable to CINV.Three personalized prediction models were well-validated and could be used to optimize antiemetic therapy for individual patients.

Establishment of Person and Enterprise Process Model in Product Data Management System

Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.

Emerging personalized virtual brain models: next-generation resection neurosurgery for drug-resistant epilepsy?

Recently,a novel workflow known as the virtual epileptic patient(VEP)has been proposed by a research team from Aix Marseille Universitéin their papers published in Lancet Neurology,Science Translational Medicine and Epilepsia.This method involves creating an individualized virtual brain model based on computational modelling,which can facilitate clinical decision-making by estimating the epileptogenic zone and performing the virtual surgery.Here,we summarize brief workflow,strengths,and limitations of VEP,as well as its performance in a retrospective study of 53 patients with drug-resistant focal epilepsy who underwent stereoelectroencephalography.A large-scale clinical trial(NCT03643016)is underway to further assess VEP,which is expected to enroll 356 patients prospectively.As supporting evidence accumulates,the clinical application of VEP has the potential to improve clinical practice,leading to better outcomes and qualities of life of patients.

Data-driven comparison of federated learning and model personalization for electric load forecasting

Residential short-term electric load forecasting is essential in modern decentralized power systems.Load forecasting methods mostly rely on neural networks and require access to private and sensitive electric load data for model training.Conventional neural network training aggregates all data on a centralized server to train one global model.However,the aggregation of user data introduces security and data privacy risks.In contrast,this study investigates the modern neural network training methods of federated learning and model personalization as potential solutions to security and data privacy problems.Within an extensive simulation approach,the investigated methods are compared to the conventional centralized method and a pre-trained baseline predictor to compare their respective performances.This study identifies that the underlying data structure of electric load data has a significant influence on the loss of a model.We therefore conclude that a comparison of loss distributions will in fact be considered a comparison of data structures,rather than a comparison of the model performance.As an alternative method of comparison of loss values,this study develops the"differential comparison".The method allows for the isolated comparison of model loss differences by only comparing the losses of two models generated by the same data sample to build a distribution of differences.The differential comparison method was then used to identify model personalization as the best performing model training method for load forecasting among all analyzed methods,with a superior performance in 59.1%of all cases.

Advances in medical decision support systems for diagnosis of acute graft-versus-host disease: molecular and computational intelligence joint approaches

Acute graft-versus-host disease (aGVHD) is a serious systemic complication of allogeneic hematopoietic stemcell transplantation (HSCT) causing considerable morbidity and mortality. Acute GVHD occurs when alloreactivedonor-derived T cells recognize host-recipient antigens as foreign. These trigger a complex multiphase process thatultimately results in apoptotic injury in target organs. The early events leading to GVHD seem to occur very soon,presumably within hours from the graft infusion. Therefore, when the first signs of aGVHD clinically manifest, thedisease has been ongoing for several days at the cellular level, and the inflammatory cytokine cascade is fully activated.So, it comes as no surprise that progress in treatment based on clinical diagnosis of aGVHD has been limited in the past30 years. It is likely that a pre-emptive strategy using systemic high-dose corticosteroids as early as possible couldimprove the outcome of aGVHD. Due to the deleterious effects of such treatment particularly in terms of infection riskposed by systemic steroid administration in a population that is already immune-suppressed, it is critical to identifybiomarker signatures for approaching this very complex task. Some research groups have begun addressing this issuethrough molecular and proteomic analyses, combining these approaches with computational intelligence techniques,with the specific aim of facilitating the identification of diagnostic biomarkers in aGVHD. In this review, we focus on theaGVHD scenario and on the more recent state-of-the-art.We also attempt to give an overview of the classical and noveltechniques proposed as medical decision support system for the diagnosis of GVHD.

Optimal Treatment Cost Allocation Methods in Pollution Control

Totalemission controlis an effective pollution controlstrategy.However, Chinese application oftotal emission controllacks reasonable and fair methodsfor optimaltreatment cost allocation,a criticalissue in total emission control.This paper considersfour approachesto allocate treatmentcosts.Thefirstapproachisto setup a multiple objective planning model and to solve the model using the shortest distance ideal point method. The second approachisto define degree ofsatisfaction for cost allocation resultsfor each polluter and to establish a method based onthisconcept.Thethirdisto apply bargaining and arbitrationtheoryto develop a model.Thefourth isto establish a cooperative N person game model which can be solved usingthe Shapley value method,the core method,the Cost Gap Allocation method orthe Minimum Costs Remaining Savings method.These approaches are compared using a practicable case study.

Personality correlates of reporting Chinese words from the Deutsch "high-low" word illusion by Chinese-speaking people

Objective When English-speaking people listen to the Deutsch ＂high-low＂ word illusion, they report hearing English words. Whether Chinese-speaking people report Chinese words when listening to the illusion, or whether any reported words might be correlated with personality traits as previous investigations have demonstrated for listening to music in other cultures, is open to question. The present study aimed to address this. Methods A total of 308 right-handed, healthy volunteers （177 women and 131 men） were given the illusion test and asked to answer the Zuckerman-Kuhlman personality questionnaire （ZKPQ）. Their depressive tendency was measured by the Plutchik-van Praag depression inventory （PVP）. Results There was no gender effect regarding either the PVP score or the number of reported Chinese words from the illusion. Women scored higher on ZKPQ neuroticism-anxiety than men. The number of meaningful Chinese words reported was correlated with the ZKPQ impulsive sensation-seeking, aggression-hostility, and activity scores. Some words reported by participants who scored higher on these three traits were related in meaning to those scales. Conclusion Our preliminary results suggest that when Chinese-speaking people listen to the Deutsch ＂high-low＂ word illusion, they might use personality-related, specific cognitive schemata.