Methods—We used data on risk factor exposure by country, age group, and sex from pooled analysis of population-based health surveys. Relative risks for cause-specific mortality were obtained from pooling of large prospective studies. We calculated the population attributable fractions (PAF) for each risk factor alone, and for the combination of all risk factors, accounting for multi-causality a...

Insurance market reforms face the key challenge of addressing the threat that risk selection poses to the availability, of stable, high-value insurance policies that provide long-term risk protection. Many of the strategies in use today fail to address this breakdown in risk pooling, and some even exacerbate it. Flexible risk adjustment schemes are a promising avenue for promoting market stabil...

Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this...

OBJECTIVES To examine the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and the risk of heart failure or hospital admission for heart failure in patients with type 2 diabetes. DESIGN Systematic review and meta-analysis of randomised and observational studies. DATA SOURCES Medline, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov searched up to 2...

Graph neural networks (GNNs) have demonstrated a significant success in various graph learning tasks, from classification to anomaly detection. There recently has emerged number of approaches adopting pooling operation within GNNs, with goal preserve attributive and structural features during the representation learning. However, most existing operations suffer limitations relying on node-wise ...