Infectious Disease

Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.

Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase chain reaction (RT-PCR) offers quick results, chest X-ray (CXR) imaging is a more reliable method for disease classification and assessment. The rapid sp...

Classifying chest CT images as COVID-19 positive/negative using a convolutional neural network ensemble model and uniform experimental design method.

BACKGROUND: To classify chest computed tomography (CT) images as positive or negative for coronavirus disease 2019 (COVID-19) quickly and accurately, researchers attempted to develop effective models by using medical images.

Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases.

The search for effective drugs to treat new and existing diseases is a laborious one requiring a large investment of capital, resources, and time. The...

The regulatory and modulatory roles of TRP family channels in malignant tumors and relevant therapeutic strategies.

Transient receptor potential (TRP) channels are one primary type of calcium (Ca) permeable channels, and those relevant transmembrane and intracellula...

The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.

BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, thei...

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.

Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle a...

Self-Ensembling Co-Training Framework for Semi-Supervised COVID-19 CT Segmentation.

The coronavirus disease 2019 (COVID-19) has become a severe worldwide health emergency and is spreading at a rapid rate. Segmentation of COVID lesions...

COVID-19 Screening in Chest X-Ray Images Using Lung Region Priors.

Early screening of COVID-19 is essential for pandemic control, and thus to relieve stress on the health care system. Lung segmentation from chest X-ra...

A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images.

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as cough or fever, which in severe cases can cause p...

A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images.

Coronavirus disease-19 (COVID-19) is a severe respiratory viral disease first reported in late 2019 that has spread worldwide. Although some wealthy c...

Accuracy of deep learning-based computed tomography diagnostic system for COVID-19: A consecutive sampling external validation cohort study.

Ali-M3, an artificial intelligence program, analyzes chest computed tomography (CT) and detects the likelihood of coronavirus disease (COVID-19) based...

Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC...

Integrating mechanistic and deep learning models for accurately predicting the enrichment of polyhydroxyalkanoates accumulating bacteria in mixed microbial cultures.

The enrichment of polyhydroxyalkanoates (PHA) accumulating bacteria (PAB) in mixed microbial cultures (MMC) is extremely difficult to be predicted and...

EpistoNet: an ensemble of Epistocracy-optimized mixture of experts for detecting COVID-19 on chest X-ray images.

The Coronavirus has spread across the world and infected millions of people, causing devastating damage to the public health and global economies. To ...

Application potential of biogenically synthesized silver nanoparticles using L. extracts as pharmaceuticals and catalysts for organic pollutant degradation.

This study was designed to evaluate the optimal conditions for the eco-friendly synthesis of silver nanoparticles (AgNPs) using L. (Lythraceae) aqueo...

Predicting increases in COVID-19 incidence to identify locations for targeted testing in West Virginia: A machine learning enhanced approach.

During the COVID-19 pandemic, West Virginia developed an aggressive SARS-CoV-2 testing strategy which included utilizing pop-up mobile testing in loca...

Robotic Puboprostatic Fistula Repair with Holmium Laser Pubic Debridement.

INTRODUCTION AND OBJECTIVE: Urosymphyseal fistula (UF) with osteomyelitis most commonly occurs as a result of prostate cancer and benign prostate hype...

COVID-19 Case Recognition from Chest CT Images by Deep Learning, Entropy-Controlled Firefly Optimization, and Parallel Feature Fusion.

In healthcare, a multitude of data is collected from medical sensors and devices, such as X-ray machines, magnetic resonance imaging, computed tomogra...

A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19).

COVID-19 has had a detrimental impact on normal activities, public safety, and the global financial system. To identify the presence of this disease w...

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integr...