Infectious Disease

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models.

There is increasing interest in the use of mechanism-based multi-scale computational models (such as agent-based models (ABMs)) to generate simulated clinical populations in order to discover and evaluate potential diagnostic and therapeutic modalities. The description of the environment in which a biomedical simulation operates (model context) and parameterization of internal model rules (model c...

Machine-Learning Single-Stranded DNA Nanoparticles for Bacterial Analysis.

A two-dimensional nanoparticle-single-stranded DNA (ssDNA) array has been assembled for the detection of bacterial species using machine-learning (ML) algorithms. Out of 60 unknowns prepared from bacterial lysates, 54 unknowns were predicted correctly. Furthermore, the nanosensor array, supported by ML algorithms, was able to distinguish wild-type from its mutant by a single gene difference. In a...

Artificial Intelligence Applied to Chest X-Ray Images for the Automatic Detection of COVID-19. A Thoughtful Evaluation Approach.

Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ra...

Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine.

The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source trac...

Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test.

BACKGROUND: The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, vira...

Deep learning for sensitive detection of Helicobacter Pylori in gastric biopsies.

BACKGROUND: Helicobacter pylori, a 2 × 1 μm spiral-shaped bacterium, is the most common risk factor for gastric cancer worldwide. Clinically, patients...

Identification of biological correlates associated with respiratory failure in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global public health concern. Recently, a genome-wide association study (GWAS) was performed with...

Quality control, HPTLC analysis, antioxidant and antimicrobial activity of hydroalcoholic extract of roots of ( C.B Clarke).

OBJECTIVES: , CB Clarke () is a perennial herb of the Compositae family. The root of has been used for the treatment of various diseases such as hepa...

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images.

The novel Coronavirus disease (COVID-19), which first appeared at the end of December 2019, continues to spread rapidly in most countries of the world...

Hepatitis C viral load and genotypes among Nigerian subjects with chronic infection and implication for patient management: a retrospective review of data.

INTRODUCTION: Hepatitis C Virus (HCV) is highly infectious with no currently available vaccine. Prior to treatment, it is recommended to confirm HCV i...

Vital signs assessed in initial clinical encounters predict COVID-19 mortality in an NYC hospital system.

Timely and effective clinical decision-making for COVID-19 requires rapid identification of risk factors for disease outcomes. Our objective was to id...

Selecting Children with Vesicoureteral Reflux Who are Most Likely to Benefit from Antibiotic Prophylaxis: Application of Machine Learning to RIVUR.

PURPOSE: Continuous antibiotic prophylaxis reduces the risk of recurrent urinary tract infection by 50% in children with vesicoureteral reflux. Howeve...

A scaffold hopping strategy to generate new aryl-2-amino pyrimidine MRSA biofilm inhibitors.

Infections that stem from bacterial biofilms are difficult to eradicate. Within a biofilm state, bacteria are upwards of 1000-fold more resistant to c...

The design and application of an automated microscope developed based on deep learning for fungal detection in dermatology.

BACKGROUND: Light microscopy to study the infection of fungi in skin specimens is time-consuming and requires automation.

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost.

BACKGROUND: Sepsis is a significant cause of mortality in-hospital, especially in ICU patients. Early prediction of sepsis is essential, as prompt and...

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), an...

Clinically applicable approach for predicting mechanical ventilation in patients with COVID-19.

BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) requiring mechanical ventilation have high mortality and resource utilisation. The abili...

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological...

Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels.

Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation and contact tracing so that the spread of infection ...

M Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging.

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preve...