Infectious Disease

DeLUCS: Deep learning for unsupervised clustering of DNA sequences.

We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural n...

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the COVID-19, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. We aim to develop a deep le...

Machine learning classification of trajectories from molecular dynamics simulations of chromosome segregation.

In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation...

Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM.

To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based S...

COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization.

The coronavirus outbreak 2019, called COVID-19, which originated in Wuhan, negatively affected the lives of millions of people and many people died fr...

ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic res...

A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis.

COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information i...

Mycobacterium abscessus drug discovery using machine learning.

The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the develope...

Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network.

In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibilit...

COVID-19 Mask Usage and Social Distancing in Social Media Images: Large-scale Deep Learning Analysis.

BACKGROUND: The adoption of nonpharmaceutical interventions and their surveillance are critical for detecting and stopping possible transmission route...

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world.

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-1...

DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics.

Improvements in microscopy software and hardware have dramatically increased the pace of image acquisition, making analysis a major bottleneck in gene...

Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT.

Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim...

A machine learning application for raising WASH awareness in the times of COVID-19 pandemic.

The COVID-19 pandemic has revealed the power of internet disinformation in influencing global health. The deluge of information travels faster than th...

Objective evaluation of deep uncertainty predictions for COVID-19 detection.

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and oth...

Scale-Adaptive Deep Model for Bacterial Raman Spectra Identification.

The combination of Raman spectroscopy and deep learning technology provides an automatic, rapid, and accurate scheme for the clinical diagnosis of pat...

Mix-and-Interpolate: A Training Strategy to Deal With Source-Biased Medical Data.

Till March 31st, 2021, the coronavirus disease 2019 (COVID-19) had reportedly infected more than 127 million people and caused over 2.5 million deaths...

Detection of COVID-19 With CT Images Using Hybrid Complex Shearlet Scattering Networks.

With the ongoing worldwide coronavirus disease 2019 (COVID-19) pandemic, it is desirable to develop effective algorithms to automatically detect COVID...

Prediction of post-stroke urinary tract infection risk in immobile patients using machine learning: an observational cohort study.

BACKGROUND: Urinary tract infection (UTI) is one of major nosocomial infections significantly affecting the outcomes of immobile stroke patients. Prev...

Using a Deep Learning Model to Explore the Impact of Clinical Data on COVID-19 Diagnosis Using Chest X-ray.

The coronavirus pandemic (COVID-19) is disrupting the entire world; its rapid global spread threatens to affect millions of people. Accurate and timel...