BACKGROUND Fat embolism in the deep retinal capillary plexus is one of the reported mechanisms underlying central/paracentral scotoma in patients with Purtscher's retinopathy. Here we report the clear delineation of capillary dropout in the deep capillary plexus using optical coherence tomography angiography (OCTA) in a chronic case of unexplained scotoma that developed after femoral fracture. ...

Do Tertiary Dropout Students Really Not Succeed in European Labour Markets? Tertiary education has been expanding hugely over the last decades, so that tertiary dropout students will constitute a growing distinctive group in future labour markets. University dropout is regularly discussed as a ‘negative’ indicator in terms of reinforcing socio-economic inequalities and being a sign of universit...

The aim was to investigate predictors of treatment dropout among 182 children (aged 8-15 years) participating in an effectiveness trial of manual-based 10-session individual and group cognitive behavior therapy (CBT) for anxiety disorders in community clinics. The dropout rate was 14.4%, with no significant difference between the two treatment conditions. We examined predictors for overall drop...

BACKGROUND Rates of treatment dropout in outpatient Dialectical Behavior Therapy (DBT) in the community can be as high as 24 % to 58 %, making dropout a great concern. The primary purpose of this article was to examine predictors of dropout from DBT in a community mental health setting. METHODS Participants were 56 consumers with borderline personality disorder (BPD) who were psychiatrically ...

Dropout has been witnessed with great success in training deep neural networks by independently zeroing out the outputs of neurons at random. It has also received a surge of interest for shallow learning, e.g., logistic regression. However, the independent sampling for dropout could be suboptimal for the sake of convergence. In this paper, we propose to use multinomial sampling for dropout, i.e...

Dropout is one of the key techniques to prevent the learning from overfitting. It is explained that dropout works as a kind of modified L2 regularization. Here, we shed light on the dropout from Bayesian standpoint. Bayesian interpretation enables us to optimize the dropout rate, which is beneficial for learning of weight parameters and prediction after learning. The experiment result also enco...

In this paper, multivariate skew-normal distribution is em- ployed for analyzing an outcome based dropout model for repeated mea- surements with non-random dropout in skew regression data sets. A probit regression is considered as the conditional probability of an ob- servation to be missing given outcomes. A simulation study of using the proposed methodology and comparing it with a semi-parame...

We introduce Information Dropout, a generalization of dropout that is motivated by the Information Bottleneck principle and highlights the way in which injecting noise in the activations can help in learning optimal representations of the data. Information Dropout is rooted in information theoretic principles, it includes as special cases several existing dropout methods, like Gaussian Dropout ...

BACKGROUND Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether. OBJECTIVE To propose a concep...