Infectious Disease

A Ligand-Based Virtual Screening Method Using Direct Quantification of Generalization Ability.

Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient when dealing with such problems where the data are imbalanced and features describing the chemical characteristic of ligands are high-dimensional. We here describe a machine learning algorithm LBS (local beta screening) for ligand-based virtual screen...

Morphology-based classification of mycobacteria-infected macrophages with convolutional neural network: reveal EsxA-induced morphologic changes indistinguishable by naked eyes.

EsxA is an essential virulence factor for Mycobacterium tuberculosis (Mtb) pathogenesis as well as an important biomarker for Mtb detection. In this study, we use light microscopy and deep learning-based image analysis to classify the morphologic changes of macrophages infected by Mycobacterium marinum (Mm), a surrogate model for Mtb. Macrophages were infected either with the mCherry-expressing Mm...

Incorporating Conversational Strategies in a Social Robot to Interact with People with Dementia.

BACKGROUND: Socially assistive robots (SARs) have the potential to assist nonpharmacological interventions based on verbal communication to support th...

mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology.

Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSp...

Sorghum Fermented by NK Enhances Inhibition of Vascular Inflammation in TNF-α-stimulated Human Aortic Smooth Muscle Cells.

Sorghum bicolor L. Moench is widely grown all over the world for food and feed. The effects of sorghum extracts on general inflammation have been pr...

Accurate and cost-effective prediction of HBsAg titer in industrial scale fermentation process of recombinant Pichia pastoris by using neural network based soft sensor.

In the current work, the attempt was made to apply best-fitted artificial neural network (ANN) architecture and the respective training process for pr...

A neural network model predicts community-level signaling states in a diverse microbial community.

Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in hetero...

A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats.

Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the prel...

DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in .

Seeing is believing. The direct observation of GFP-Atg8 vacuolar delivery under confocal microscopy is one of the most useful end-point measurements f...

Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and qua...

Stereo Vision Based Sensory Substitution for the Visually Impaired.

The development of computer vision based systems dedicated to help visually impaired people to perceive the environment, to orientate and navigate has...

Effects of different moisture and temperature levels on survival in poultry fat.

Fat products have been historically thought to have too low water activity to harbor pathogens. However, it has been recently reported that high moist...

Conservation region finding for influenza A viruses by machine learning methods of N-linked glycosylation sites and B-cell epitopes.

Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous threat to human health worldwide. It leads to high mo...

Using natural language processing and VetCompass to understand antimicrobial usage patterns in Australia.

BACKGROUND: Currently there is an incomplete understanding of antimicrobial usage patterns in veterinary clinics in Australia, but such knowledge is c...

SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.

Machine learning holds considerable promise for understanding complex biological processes such as vaccine responses. Capturing interindividual variab...

Effects of extended-release eprinomectin on fescue toxicosis, performance, and reproduction on fall-calving beef cows.

The objective of this experiment was to evaluate effects of extended-release eprinomectin on fescue toxicosis and impacts on performance and reproduct...

An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time req...

Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance.

Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB)...

An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies.

BACKGROUND: Antimicrobial peptides (AMPs) are essential components of the innate immune system and can protect the host from various pathogenic bacter...

Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA.

Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant economic and public health impacts necessitate develo...