Infectious Disease

Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs.

Using administrative data on all Veterans who enter Department of Veterans Affairs (VA) medical centres throughout the USA, this paper uses artificial intelligence (AI) to predict mortality rates for patients with COVID-19 between March and August 2020. First, using comprehensive data on over 10 000 Veterans' medical history, demographics and lab results, we estimate five AI models. Our XGBoost mo...

Machine learning modeling of the effects of media formulated with various yeast extracts on heterologous protein production in Escherichia coli.

In microbial manufacturing, yeast extract is an important component of the growth media. The production of heterologous proteins often varies because of the yeast extract composition. To identify why this reduces protein production, the effects of yeast extract composition on the growth and green fluorescent protein (GFP) production of engineered Escherichia coli were investigated using a deep neu...

A novel reassortant avian influenza H4N6 virus isolated from an environmental sample during a surveillance in Maharashtra, India.

BACKGROUND & OBJECTIVES: Low pathogenic avian influenza (LPAI) viruses cause mild clinical illness in domestic birds. Migratory birds are a known rese...

Performance of SURF and SIFT Keypoints for the Automated Differentiation of Abnormality in Chest Radiographs.

In this work, automated abnormality detection using keypoint information from Speeded-Up Robust feature (SURF) and Scale Invariant Feature Transform (...

COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning.

Medical imaging offers great potential for COVID-19 diagnosis and monitoring. Our work introduces an automated pipeline to segment areas of COVID-19 i...

Deep Learning Methods to Predict Mortality in COVID-19 Patients: A Rapid Scoping Review.

The ongoing COVID-19 pandemic has become the most impactful pandemic of the past century. The SARS-CoV-2 virus has spread rapidly across the globe aff...

DIAG a Diagnostic Web Application Based on Lung CT Scan Images and Deep Learning.

Coronavirus disease is a pandemic that has infected millions of people around the world. Lung CT-scans are effective diagnostic tools, but radiologist...

On the Efficiency of Machine Learning Models in Malaria Prediction.

Malaria is still a real public health concern in Sub-Saharan African countries such as Senegal where it represents approximately 35% of the consultati...

Mobile Remote Presence Robots for Medical Consultation and Social Connectedness.

We demonstrate that Mobile Remote Presence systems (MRP) aka telepresence robots can be successfully used in certain types of medical consultation suc...

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.

Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, ...

A large-scale investigation and identification of methicillin-resistant Staphylococcus aureus based on peaks binning of matrix-assisted laser desorption ionization-time of flight MS spectra.

Recent studies have demonstrated that the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) could be used to...

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

Deep learning is an important branch of artificial intelligence that has been successfully applied into medicine and two-dimensional ligand design. Th...

Digital holographic deep learning of red blood cells for field-portable, rapid COVID-19 screening.

Rapid screening of red blood cells for active infection of COVID-19 is presented using a compact and field-portable, 3D-printed shearing digital holog...

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis...

[A preliminary investigation on a deep learning convolutional neural networks based pulmonary tuberculosis CT diagnostic model].

To evaluate the clinical value of a pulmonary tuberculosis CT diagnostic model based on deep learning convolutional neural networks (CNN). From Marc...

Future perspectives of robot psychiatry: can communication robots assist psychiatric evaluation in the COVID-19 pandemic era?

PURPOSE OF REVIEW: Direct face-to-face interview between a psychiatrist and a patient is crucial in psychiatric evaluation, however, such traditional ...

Identifying HIV-related digital social influencers using an iterative deep learning approach.

OBJECTIVES: Community popular opinion leaders have played a critical role in HIV prevention interventions. However, it is often difficult to identify ...

Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in p...

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2....

Deep learning applied to lung ultrasound videos for scoring COVID-19 patients: A multicenter study.

In the current pandemic, lung ultrasound (LUS) played a useful role in evaluating patients affected by COVID-19. However, LUS remains limited to the v...