Infectious Disease

COVID-19 and the epistemology of epidemiological models at the dawn of AI.

The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable statistical models to estimate the strength/direction of (potentially causal) between variables (through 'causal inference'), and the (past/future) ...

Comparative study of antibacterial activity between Schiff base nicotinic hydrazide derivative and its silver architected nanoparticles with atomic force microscopic study of bacterial cell wall.

The threat of multi-drug resistant bacterial pathogens evokes researchers to synthesized safe and effective chemotherapeutic agents for nano-drug delivery system. In current study, Schiff base of nicotinic hydrazide(NHD) and its silver nanoparticles(NHD-AgNPs) were synthesized and characterized. These compounds were investigated for cytotoxicity, antibacterial and AFM activity. The NHD showed LD50...

Anti-inflammatory and antibacterial activities of P. petiolosa (Christ) Ching ethyl acetate extract against S. aureus in mice.

P. petiolosa as a typical Chinese herbal medicine has been generally utilized as Chinese native medicine formulation for treatment of chronic bronchit...

Antimicrobial and synergistic activity of thiazoline derivatives in combination with conventional antibiotics against multidrug resistant Staphylococcus aureus isolated from abscess drainage samples.

Emergence and spread of multidrug resistant (MDR) Staphylococcus aureus strains is becoming major challenge in treatment of soft tissue infections. Th...

A fatal invasive pulmonary infection in an adult patient with malignant lung adenocarcinoma.

BACKGROUND AND PURPOSE: complex as a ubiquitous environmental mold is increasingly reported to cause an invasive fungal infection in immunosuppressiv...

Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV.

BACKGROUND: Frailty is an important clinical concern for the aging population of people living with HIV (PLWH). The objective of this study was to ide...

An artificial intelligence approach to COVID-19 infection risk assessment in virtual visits: A case report.

OBJECTIVE: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used...

Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases.

OBJECTIVE: As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for h...

'I'm over the moon!': patient-perceived outcomes of hepatitis C treatment.

Understanding patient-perceived outcomes is crucial for assessing the effectiveness and acceptability of hepatitis C virus (HCV) treatment. This study...

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a C...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate sc...

Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and...

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images.

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung...

A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis.

COVID-19 has caused a global pandemic and become the most urgent threat to the entire world. Tremendous efforts and resources have been invested in de...

A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.

Segmentation of pneumonia lesions from CT scans of COVID-19 patients is important for accurate diagnosis and follow-up. Deep learning has a potential ...

Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.

Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution...

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.

Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-b...

Signs of the times: universalism and localism.

At a time when nationalism has reappeared in Europe, when COVID-19 is not yet quarantined and when compassion coexists with grief, there is a need to ...

Systematic analysis of supervised machine learning as an effective approach to predicate β-lactam resistance phenotype in Streptococcus pneumoniae.

Streptococcus pneumoniae is the most common human respiratory pathogen, and β-lactam antibiotics have been employed to treat infections caused by S. p...

Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.

BACKGROUND: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues...