-
Article
Open AccessChronic COVID-19 infection in an immunosuppressed patient shows changes in lineage over time: a case report
The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 virus, emerged in late 2019 and spready globally. Many effects of infection with this pathogen are still unknown, with both ...
-
Chapter and Conference Paper
StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN
Deep conditional generative models are excellent tools for creating high-quality images and editing their attributes. However, training modern generative models from scratch is very expensive and requires larg...
-
Article
Open AccessEosinophil-independent IL-5 levels are increased in critically ill COVID-19 patients who survive
-
Article
Open AccessChildren hospitalized with community-acquired pneumonia complicated by effusion: a single-centre retrospective cohort study
To describe children hospitalized with community-acquired pneumonia complicated by effusion (cCAP).
-
Chapter and Conference Paper
r-softmax: Generalized Softmax with Controllable Sparsity Rate
Nowadays artificial neural network models achieve remarkable results in many disciplines. Functions map** the representation provided by the model to the probability distribution are the inseparable aspect o...
-
Chapter and Conference Paper
Contrastive Hierarchical Clustering
Deep clustering has been dominated by flat models, which split a dataset into a predefined number of groups. Although recent methods achieve an extremely high similarity with the ground truth on popular benchm...
-
Chapter and Conference Paper
ChiENN: Embracing Molecular Chirality with Graph Neural Networks
Graph Neural Networks (GNNs) play a fundamental role in many deep learning problems, in particular in cheminformatics. However, typical GNNs cannot capture the concept of chirality, which means they do not dis...
-
Article
Integrating programmable DNAzymes with electrical readout for rapid and culture-free bacterial detection using a handheld platform
The detection and identification of bacteria currently rely on enrichment steps such as bacterial culture and nucleic acid amplification to increase the concentration of target analytes. These steps increase a...
-
Article
Open AccessAssessment of nasopharyngeal Streptococcus pneumoniae colonization does not permit discrimination between Canadian children with viral and bacterial respiratory infection: a matched-cohort cross-sectional study
Readily-available diagnostics do not reliably discriminate between viral and bacterial pediatric uncomplicated pneumonia, both of which are common. Some have suggested that assessment of pneumococcal carriage ...
-
Article
Open AccessComparison of four COVID-19 screening strategies to facilitate early case identification within the homeless shelter population: A structured summary of a study protocol for a randomised controlled trial
1. To compare the effectiveness of four different surveillance strategies in detecting COVID-19 within the homeless shelter population.
-
Article
Open AccessAuthor Correction: The Use of Motion Analysis as Particle Biomarkers in Lensless Optofluidic Projection Imaging for Point of Care Urine Analysis
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
-
Article
Open AccessPointed Subspace Approach to Incomplete Data
Incomplete data are often represented as vectors with filled missing attributes joined with flag vectors indicating missing components. In this paper, we generalize this approach and represent incomplete data ...
-
Chapter and Conference Paper
Iterative Imputation of Missing Data Using Auto-Encoder Dynamics
This paper introduces an approach to missing data imputation based on deep auto-encoder models, adequate to high-dimensional data exhibiting complex dependencies, such as images. The method exploits the proper...
-
Chapter and Conference Paper
Processing of Incomplete Images by (Graph) Convolutional Neural Networks
We investigate the problem of training neural networks from incomplete images without replacing missing values. For this purpose, we first represent an image as a graph, in which missing pixels are entirely ig...
-
Chapter and Conference Paper
Spatial Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have recently become the primary choice for learning from graph-structured data, superseding hash fingerprints in representing chemical compounds. However, GCNs lack the abi...
-
Chapter and Conference Paper
Estimating Conditional Density of Missing Values Using Deep Gaussian Mixture Model
We consider the problem of estimating the conditional probability distribution of missing values given the observed ones. We propose an approach, which combines the flexibility of deep neural networks with the...
-
Article
Open AccessThe Use of Motion Analysis as Particle Biomarkers in Lensless Optofluidic Projection Imaging for Point of Care Urine Analysis
Urine testing is an essential clinical diagnostic tool. The presence of urine sediments, typically analyzed through microscopic urinalysis or cell culture, can be indicative of many diseases, including bacteri...
-
Article
Open AccessThe prevalence and clinical characteristics of pertussis-associated pneumonia among infants in Botswana
There are scant data on the prevalence and clinical course of pertussis disease among infants with pneumonia in low- and middle-income countries. While pertussis vaccination coverage is high (≥90%) among infan...
-
Article
Open AccessEfficient mixture model for clustering of sparse high dimensional binary data
Clustering is one of the fundamental tools for preliminary analysis of data. While most of the clustering methods are designed for continuous data, sparse high-dimensional binary representations became very po...
-
Article
Open AccessSVM with a neutral class
In many real binary classification problems, in addition to the presence of positive and negative classes, we are also given the examples of third neutral class, i.e., the examples with uncertain or intermedia...
