Role of intelligent/interactive qualitative and quantitative analysisthree-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation

BACKGROUND Donor-recipient size mismatch(DRSM)is considered a crucial factor for poor outcomes in liver transplantation(LT)because of complications,such as massive intraoperative blood loss(IBL)and early allograft dysfunction(EAD).Liver volumetry is performed routinely in living donor LT,but rarely in deceased donor LT(DDLT),which amplifies the adverse effects of DRSM in DDLT.Due to the various shortcomings of traditional manual liver volumetry and formula methods,a feasible model based on intelligent/interactive qualitative and quantitative analysis-three-dimensional(IQQA-3D)for estimating the degree of DRSM is needed.AIM To identify benefits of IQQA-3D liver volumetry in DDLT and establish an estimation model to guide perioperative management.METHODS We retrospectively determined the accuracy of IQQA-3D liver volumetry for standard total liver volume(TLV)(sTLV)and established an estimation TLV(eTLV)index(eTLVi)model.Receiver operating characteristic(ROC)curves were drawn to detect the optimal cut-off values for predicting massive IBL and EAD in DDLT using donor sTLV to recipient sTLV(called sTLVi).The factors influencing the occurrence of massive IBL and EAD were explored through logistic regression analysis.Finally,the eTLVi model was compared with the sTLVi model through the ROC curve for verification.RESULTS A total of 133 patients were included in the analysis.The Changzheng formula was accurate for calculating donor sTLV(P=0.083)but not for recipient sTLV(P=0.036).Recipient eTLV calculated using IQQA-3D highly matched with recipient sTLV(P=0.221).Alcoholic liver disease,gastrointestinal bleeding,and sTLVi>1.24 were independent risk factors for massive IBL,and drug-induced liver failure was an independent protective factor for massive IBL.Male donor-female recipient combination,model for end-stage liver disease score,sTLVi≤0.85,and sTLVi≥1.32 were independent risk factors for EAD,and viral hepatitis was an independent protective factor for EAD.The overall survival of patients in the 0.85<sTLVi<1.32 group was better compared to the sTLVi≤0.85 group and sTLVi≥1.32 group(P<0.001).There was no statistically significant difference in the area under the curve of the sTLVi model and IQQA-3D eTLVi model in the detection of massive IBL and EAD(all P>0.05).CONCLUSION IQQA-3D eTLVi model has high accuracy in predicting massive IBL and EAD in DDLT.We should follow the guidance of the IQQA-3D eTLVi model in perioperative management.

DATA: Digital Archiving and Transformed Analytics

As cloud service becomes more and more capable, available and powerful, wiseCIO has emerged from an innovative roadmap toward archival Content Management Service (aCMS) and massive Content Delivery Service (mCDS) in support of Anything-as-a-Service (XaaS) via Digital Archiving and Transformed Analytics (DATA);DATA aims to automate UBC with FAST solutions throughout a feasible, analytical, scalable and testable approach. This paper, based on the novel wiseCIO (web-based intelligent service engaging Cloud Intelligence Outlet), presents digital archiving and transformed analytics via machine learning automata for intelligent UBC processes to liaise with Universal interface for human-computer interaction, enable Brewing aggregation (differing from traditional web browsing), and engage Centered user experience. As one of the most practical aspects of artificial intelligence, machine learning is applied to analytical model building and massive and/or multidimensional Online Analytical Processing (mOLAP) for more intelligent cloud service with little explicit coding required. DATA is central to useful information via archival transformation and analytics, and utilizable intelligence for Business, Education and Entertainment (iBEE) in support of decision-making. As a result, DATA orchestrates wiseCIO to promote ACTiVE XaaS that enables accessibility, contextuality and traceability of information for vast engagement with various cloud services, such as aCMS (archival Content Management Service), COSA (Context-Oriented Screening Aggregation), DASH (Deliveries Assembled for fast Search and Hits), OLAS (Online Learning via Analytical Synthesis), REAP (Rapid Extension and Active Presentation), and SPOT (Special Points On Top) with great ease.

Research progress of artificial psychology and artificial emotion in China

Since the concept of artificial psychology and artificial emotion was first presented, it has become a topic of interest in academic circles and enterprises. In this article, we first briefly introduce the basic concepts and principles of artificial psychology and artificial emotion, analyzing the unified macro-model of the cross-disciplinary system architecture against the need-motivation-behavior framework. Second, we discuss the origin of artificial psychology and artificial emotion, its course of development, and its present situation in China. We also present a review of the published papers and research endeavors of Chinese universities and research institutions and the technical engineering applications of artificial psychology and artificial emotion. Finally, we summarize the challenges to the further development of artificial psychology and artificial emotion and our recommendations for improving the cognitive computing model of psychological states and developing reliable and accurate humanoid interaction and cooperation technology, robot platforms with emotions and humanoid interaction and cooperation capabilities, and humanoid robots for the elderly and the disabled in smart homes. We believe that, with intensive research, artificial psychology and artificial emotion may be developed further and may eventually reach maturity.