Environmental Health

Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving beyond Classification in Precision Livestock.

Previous research has shown that sensors monitoring lying behaviours and feeding can detect early signs of ill health in calves. There is evidence to suggest that monitoring change in a single behaviour might not be enough for disease prediction. In calves, multiple behaviours such as locomotor play, self-grooming, feeding and activity whilst lying are likely to be informative. However, these beha...

Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy.

Artificial intelligence (AI) and its application in medicine has grown large interest. Within gastrointestinal (GI) endoscopy, the field of colonoscopy and polyp detection is the most investigated, however, upper GI follows the lead. Since endoscopy is performed by humans, it is inherently an imperfect procedure. Computer-aided diagnosis may improve its quality by helping prevent missing lesions a...

Assessing the signal quality of electrocardiograms from varied acquisition sources: A generic machine learning pipeline for model generation.

BACKGROUND AND OBJECTIVE: Long-term electrocardiogram monitoring comes at the expense of signal quality. During unconstrained movements, the electroca...

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...

Scaffold-Constrained Molecular Generation.

One of the major applications of generative models for drug discovery targets the lead-optimization phase. During the optimization of a lead series, i...

Machine learning approach for predicting Fusarium culmorum and F. proliferatum growth and mycotoxin production in treatments with ethylene-vinyl alcohol copolymer films containing pure components of essential oils.

Fusarium culmorum and F. proliferatum can grow and produce, respectively, zearalenone (ZEA) and fumonisins (FUM) in different points of the food chain...

Automatic Detection of Flavescence Dorée Symptoms Across White Grapevine Varieties Using Deep Learning.

(FD) is a grapevine disease caused by phytoplasmas and transmitted by leafhoppers that has been spreading in European vineyards despite significant e...

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography.

Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of effective treatment and prevention of mortality; h...

Artificial intelligence in image reconstruction: The change is here.

Innovations in CT have been impressive among imaging and medical technologies in both the hardware and software domain. The range and speed of CT scan...

Application of Bayesian Additive Regression Trees for Estimating Daily Concentrations of PM Components.

Bayesian additive regression tree (BART) is a recent statistical method that combines ensemble learning and nonparametric regression. BART is construc...

Machine Learning Methods in Drug Discovery.

The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and in...

Comprehensive evaluation of the combined extracts of Epimedii Folium and Ligustri Lucidi Fructus for PMOP in ovariectomized rats based on MLP-ANN methods.

ETHNOPHARMACOLOGICAL RELEVANCE: Kidney deficiency is the main pathogenesis of osteoporosis based on the theory of "kidney governing bones" in traditio...

Deep Learning on chromatographic data for Segmentation and Sensitive Analysis.

Lateral flow immunoassay (LFIA) is one of the most common methods in point-of-care testing, which is widely applied in some conditions for various app...

Combining citizen science and deep learning for large-scale estimation of outdoor nitrogen dioxide concentrations.

Reliable estimates of outdoor air pollution concentrations are needed to support global actions to improve public health. We developed a new approach ...

Machine Learning-Guided Three-Dimensional Printing of Tissue Engineering Scaffolds.

Various material compositions have been successfully used in 3D printing with promising applications as scaffolds in tissue engineering. However, iden...

Virgin Coconut Oil-Induced Neuroprotection in Lipopolysaccharide-Challenged Rats is Mediated, in Part, Through Cholinergic, Anti-Oxidative and Anti-Inflammatory Pathways.

Neuroinflammation is associated with neuronal cell death and could lead to chronic neurodegeneration. This study investigated the neuroprotective pote...

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distrib...

The in vitro toxicity evaluation of halloysite nanotubes (HNTs) in human lung cells.

Halloysite nanotubes (HNTs) have been increasingly used in many industrial and biomedical fields. Therefore, the assessment of risk and consequences o...

Effect of silver nanospheres and nanowires on human airway smooth muscle cells: role of sulfidation.

: The toxicity of inhaled silver nanoparticles on contractile and pro-inflammatory airway smooth muscle cells (ASMCs) that control airway calibre is u...

Machine learning-based QSAR models to predict sodium ion channel (Na 1.5) blockers.

Conventional experimental approaches used for the evaluation of the proarrhythmic potential of compounds in the drug discovery process are expensive ...