Infectious Disease

Engineering Biorthogonal Phage-Based Nanobots for Ultrasensitive, Bacteria Detection.

Advances in synthetic biology, nanotechnology, and genetic engineering are allowing parallel advances in areas such as drug delivery and rapid diagnostics. Although our current visions of nanobots may be far off, a generation of nanobots synthesized by engineering viruses is approaching. Such tools can be used to solve complex problems where current methods do not meet current demands. Assuring sa...

A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.

Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million deaths in 2017. Treatment failure is one of a main reason behind these deaths. Reasons of treatment failure are still unknown and the death rate due to TB is increasing. Machine learning and data analytics approaches are proved to be useful in healthcare domain in finding the associations among diff...

A fully automated deep learning pipeline for high-throughput colony segmentation and classification.

Adenine auxotrophy is a commonly used non-selective genetic marker in yeast research. It allows investigators to easily visualize and quantify various...

Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation.

In recent years there has been an increasing use of satellite Earth observation (EO) data in dengue research, in particular the identification of land...

Positron emission tomography imaging in cardiovascular disease.

Positron emission tomography (PET) imaging is useful in cardiovascular disease across several areas, from assessment of myocardial perfusion and viabi...

Assessment of Expression System for Overexpression of Active Recombinant Ocriplasmin.

Ocriplasmin (Jetrea TM) is a FDA approved recombinant enzyme utilized in the treatment of vitreomacular adhesion (VMA). This is a recombinant C-termi...

Applications of machine-learning methods for the discovery of NDM-1 inhibitors.

The emergence of New Delhi metal beta-lactamase (NDM-1)-producing bacteria and their worldwide spread pose great challenges for the treatment of drug-...

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays.

BACKGROUND AND OBJECTIVE: Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus ...

A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network.

Pneumonia is a virulent disease that causes the death of millions of people around the world. Every year it kills more children than malaria, AIDS, an...

An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.

After mating, female mosquitoes need animal blood to develop their eggs. In the process of acquiring blood, they may acquire pathogens, which may caus...

The application of machine learning techniques to innovative antibacterial discovery and development.

INTRODUCTION: After the initial wave of antibiotic discovery, few novel classes of antibiotics have emerged, with the latest dating back to the 1980's...

Optical techniques, computed tomography and deep learning role in the diagnosis of COVID-19 pandemic towards increasing the survival rate of vulnerable populations.

• Severe lung complications can be explored using computed tomography during COVID-19 pandemic. • Ultra-low dose CT can enhance COVID-19 infected pati...

Machine learning-based analyses support the existence of species complexes for and .

Human strongyloidiasis is a serious disease mostly attributable to Strongyloides stercoralis and to a lesser extent Strongyloides fuelleborni, a paras...

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other comm...

Predicting dengue importation into Europe, using machine learning and model-agnostic methods.

The geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic...

Internet of things-inspired healthcare system for urine-based diabetes prediction.

Healthcare industry is the leading domain that has been revolutionized by the incorporation of Internet of Things (IoT) technology resulting in smart ...

Development and evaluation of a novel protective device for upper gastrointestinal endoscopy in the COVID-19 pandemic: the EBOX.

BACKGROUND: During the COVID-19 pandemic, aerosol-generating procedures such as upper gastrointestinal endoscopy (UGIE) have been considered high risk...

Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States.

Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 millio...

Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment.

COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming th...

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predic...