Functional clustering methods for binary longitudinal data with temporal heterogeneity

In the analysis of binary longitudinal data, it is of interest to model a dynamic relationship between a response and covariates as a function of time, while also investigating similar patterns of time-dependent interactions. We present a novel generalized varying-coefficient model that accounts for within-subject variability and simultaneously clusters varying-coefficient functions, without restricting the number of clusters nor overfitting the data. In the analysis of a heterogeneous series of binary data, the model extracts population-level fixed effects, cluster-level varying effects, and subject-level random effects. Various simulation studies show the validity and utility of the proposed method to correctly specify cluster-specific varying-coefficients when the number of clusters is unknown. The proposed method is applied to a heterogeneous series of binary data in the German Socioeconomic Panel (GSOEP) study, where we identify three major clusters demonstrating the different varying effects of socioeconomic predictors as a function of age on the working status

URIE: Universal Image Enhancement for Visual Recognition in the Wild

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Robot-Assisted Repair of Atrial Septal Defect: A Comparison of Beating and Non-Beating Heart Surgery

© 2022, The Korean Society for Thoracic and Cardiovascular SurgeryBackground: Robot-assisted repair of atrial septal defect (ASD) can be performed under either beating-heart or non-beating-heart conditions. However, the risk of cerebral air embolism (i.e., stroke) is a concern in the beating-heart approach. This study aimed to compare the outcomes of beating and non-beating-heart approaches in robot-assisted ASD repair. Methods: From 2010 to 2019, a total of 45 patients (mean age, 43.4±14.6 years; range, 19–79 years) underwent ASD repair using the da Vinci robotic surgical system. Twenty-seven of these cases were performed on a beating heart (beating-heart group, n=27) and the other cases were performed on an arrested or fibrillating heart (non-beating-heart group, n=18). Cardiopulmonary bypass (CPB) was achieved via cannulation of the femoral vessels and the right internal jugular vein in all patients. Results: Complete ASD closure was verified using intraoperative transesophageal echocardiography in all patients. Conversion to open surgery was not performed in any cases, and there were no major complications. All patients recovered from anesthesia without any immediate postoperative neurologic symptoms. In a subgroup analysis of isolated ASD patch repair (beating-heart group: n=22 vs. non-beating-heart group: n=5), the operation time and CPB time were shorter in the beating-heart group (234±38 vs. 253±29 minutes, p=0.133 and 113±28 vs. 143±29 minutes, p=0.034, respectively). Conclusion: Robot-assisted ASD repair can be safely performed with the beating-heart approach. No additional risk in terms of cerebral embolism was found in the beating-heart group.N