Infectious Disease

Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study.

BACKGROUND: COVID-19 is a scientifically and medically novel disease that is not fully understood because it has yet to be consistently and deeply studied. Among the gaps in research on the COVID-19 outbreak, there is a lack of sufficient infoveillance data.

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.

The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the key screening approaches being radiology examination using chest radiography. It was found in early studies that patients present abnormalities in che...

Progressive multifocal leukoencephalopathy lesion and brain parenchymal segmentation from MRI using serial deep convolutional neural networks.

Progressive multifocal leukoencephalopathy (PML) is a rare opportunistic brain infection caused by the JC virus and associated with substantial morbid...

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases.

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotatio...

Piperidine based 1,2,3-triazolylacetamide derivatives induce cell cycle arrest and apoptotic cell death in .

The fungal pathogen , is a serious threat to public health and is associated with bloodstream infections causing high mortality particularly in patie...

SSP: Early prediction of sepsis using fully connected LSTM-CNN model.

BACKGROUND: Sepsis is a life-threatening condition that occurs due to the body's reaction to infections, and it is a leading cause of morbidity and mo...

Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users' perceptions.

OBJECTIVE: The potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandem...

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profil...

Facilitating the Development of Deep Learning Models with Visual Analytics for Electronic Health Records.

Electronic health record (EHR) data are widely used to perform early diagnoses and create treatment plans, which are key areas of research. We aimed t...

Comparing machine learning with case-control models to identify confirmed dengue cases.

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to dete...

-Related Infections and their Significance: A 9-Year Retrospective Study.

INTRODUCTION: is a Gram-positive, catalase- and oxidase-negative, microaerophilic, nonmotile bacteria species rarely associated with human infections...

An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study.

BACKGROUND: Prioritizing patients in need of intensive care is necessary to reduce the mortality rate during the COVID-19 pandemic. Although several s...

Ovicidal and toxicological effect of hydroalcoholic extracts of var splendens, Boiss and L. against spp.: In vitro study.

Nematodes of the Ancylostomidae family consist of important parasitic species. The control of such parasitosis represents an important challenge, give...

Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning.

BACKGROUND: Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational appr...

Detailed Analysis of Urinary Tract Infections After Robot-Assisted Radical Cystectomy.

To describe urinary tract infections (UTIs) after robot-assisted radical cystectomy (RARC) and investigate the variables associated with it. A retro...

Deep neural network to detect COVID-19: one architecture for both CT Scans and Chest X-rays.

Since December 2019, the novel COVID-19's spread rate is exponential, and AI-driven tools are used to prevent further spreading [1]. They can help pre...

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has n...

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature.

BACKGROUND: The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have respond...

The Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets.

BACKGROUND: Family violence (including intimate partner violence/domestic violence, child abuse, and elder abuse) is a hidden pandemic happening along...

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance.

The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery o...