Infectious Disease

Machine learning and artificial intelligence: applications in healthcare epidemiology.

Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a subtype of AI; it refers to the ability of computers to draw conclusions (ie, learn) from data without being directly programmed. ML builds from traditional statistical methods and has drawn significant interest in healthcare epidemiology due to its ...

Impact of COVID-19 pandemic on oil consumption in the United States: A new estimation approach.

The COVID-19 pandemic broke the balance of oil supply and demand. Meeting these oil market challenges induced by the pandemic required a more accurate assessment of the impact of the pandemic on oil consumption. The existing measurement of the impact of the pandemic on oil consumption was based on year-over-year calculation. In this work, a new measurement approach based on a comparison of simulat...

NS3/4A helicase inhibitory alkaloids from as HCV target.

Chemical investigation of roots extract, using chromatographic and spectroscopic techniques, resulted in isolation and identification of eight known ...

MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino ...

Lemongrass-Incorporated Tissue Conditioner with Adjustable Inhibitory Effect Against Candida albicans: An In Vitro Study.

PURPOSE: To develop and assess lemongrass-incorporated tissue conditioners (LG-TCs) with a potent and long-lasting inhibitory effect against Candida a...

AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs.

According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impa...

Distant Domain Transfer Learning for Medical Imaging.

Medical image processing is one of the most important topics in the Internet of Medical Things (IoMT). Recently, deep learning methods have carried ou...

PredAPP: Predicting Anti-Parasitic Peptides with Undersampling and Ensemble Approaches.

Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against parasitic diseases. Due to the fact that the experi...

Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.

BACKGROUND: Identifying interaction effects between genes is one of the main tasks of genome-wide association studies aiming to shed light on the biol...

Detection and analysis of COVID-19 in medical images using deep learning techniques.

The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied to X-ray and CT-scan medical images for ...

Recurrent Neural Network and Reinforcement Learning Model for COVID-19 Prediction.

Detection and prediction of the novel Coronavirus present new challenges for the medical research community due to its widespread across the globe. Me...

Deep-learning model for screening sepsis using electrocardiography.

BACKGROUND: Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requir...

An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.

BACKGROUND & AIMS: Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B ...

Unveiling antimicrobial activity of microalgae (UKM2), sp. (UKM8) and sp. (UKM9).

Microalgae represent promising sources of bioactive compounds for pharmaceutical and industrial applications. The emergence of antibiotic resistant ba...

Spatialising urban health vulnerability: An analysisof NYC's critical infrastructure during COVID-19.

This paper examines how fragmentation of critical infrastructure impacts the spread of the coronavirus outbreak in New York City at the neighbourhood ...

Analysis of COVID-19 severity from the perspective of coagulation index using evolutionary machine learning with enhanced brain storm optimization.

Coronavirus 2019 (COVID-19) is an extreme acute respiratory syndrome. Early diagnosis and accurate assessment of COVID-19 are not available, resulting...

Control of methicillin resistant isolated from auricular infections using aqueous and methanolic extracts of .

In the current study the potential use of aqueous and methanolic extracts of aerial parts as biological control agent against pathogenic bacteria and...

Raman spectroscopy-based adversarial network combined with SVM for detection of foodborne pathogenic bacteria.

Raman spectroscopy combined with artificial intelligence algorithms have been widely explored and focused on in recent years for food safety testing. ...

COVID-19 detection from lung CT-Scans using a fuzzy integral-based CNN ensemble.

The COVID-19 pandemic has collapsed the public healthcare systems, along with severely damaging the economy of the world. The SARS-CoV-2 virus also kn...

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients.

The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients th...