Infectious Disease

Using X-ray images and deep learning for automated detection of coronavirus disease.

Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classification system as a speedy elective finding choice to forestall COVID-19 spreading among individuals. Medical images analysis is one of the most promis...

A biochemically-interpretable machine learning classifier for microbial GWAS.

Current machine learning classifiers have successfully been applied to whole-genome sequencing data to identify genetic determinants of antimicrobial resistance (AMR), but they lack causal interpretation. Here we present a metabolic model-based machine learning classifier, named Metabolic Allele Classifier (MAC), that uses flux balance analysis to estimate the biochemical effects of alleles. We ap...

Forecasting and Evaluating Multiple Interventions for COVID-19 Worldwide.

As the Covid-19 pandemic surges around the world, questions arise about the number of global cases at the pandemic's peak, the length of the pandemic ...

The development an artificial intelligence algorithm for early sepsis diagnosis in the intensive care unit.

BACKGROUND: Severe sepsis and septic shock are still the leading causes of death in Intensive Care Units (ICUs), and timely diagnosis is crucial for t...

Dynamical footprints enable detection of disease emergence.

Developing methods for anticipating the emergence or reemergence of infectious diseases is both important and timely; however, traditional model-based...

The First Report on Pharmacokinetic/Pharmacodynamic Study of Trimethoprim/Sulfamethoxazole against Staphylococcus aureus with a Neutropenic Murine Thigh Infection Model.

INTRODUCTION: With an increase in the incidence of Staphylococcus aureus infections in the healthcare settings and in the community, trimethoprim/sulf...

Drug Resistance Prediction Using Deep Learning Techniques on HIV-1 Sequence Data.

The fast replication rate and lack of repair mechanisms of human immunodeficiency virus (HIV) contribute to its high mutation frequency, with some mut...

Machine learning to quantify habitual physical activity in children with cerebral palsy.

AIM: To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by chil...

Optimized Forecasting Method for Weekly Influenza Confirmed Cases.

Influenza epidemic is a serious threat to the entire world, which causes thousands of death every year and can be considered as a public health emerge...

Artificial intelligence approach fighting COVID-19 with repurposing drugs.

BACKGROUND: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the diseas...

Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound.

Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate D...

Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve.

The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility of healthcare and public health preparedness and p...

Differentiation of Cytopathic Effects (CPE) induced by influenza virus infection using deep Convolutional Neural Networks (CNN).

Cell culture remains as the golden standard for primary isolation of viruses in clinical specimens. In the current practice, researchers have to recog...

Fast Pathogen Identification Using Single-Cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight Mass Spectrometry Data and Deep Learning Methods.

In diagnostics of infectious diseases, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) can be applied for ...

An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases.

Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria is important for treatment. Due to the limited num...

A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

The microbiome is a new frontier for building predictors of human phenotypes. However, machine learning in the microbiome is fraught with issues of re...

iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm.

One of the most common and well studied post-transcription modifications in RNAs is N6-methyladenosine (m6A) which has been involved with a wide range...

COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System.

Background Chest radiography may play an important role in triage for coronavirus disease 2019 (COVID-19), particularly in low-resource settings. Purp...

Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets.

Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-ray (CXR) image for COVID-19 diagnosis and patient triage...

An Application of Random Walk Resampling to Phylogenetic HMM Inference and Learning.

Statistical resampling methods are widely used for confidence interval placement and as a data perturbation technique for statistical inference and le...