Environmental Health

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhib...

ToxMPNN: A deep learning model for small molecule toxicity prediction.

Machine learning (ML) has shown a great promise in predicting toxicity of small molecules. However, the availability of data for such predictions is often limited. Because of the unsatisfactory performance of models trained on a single toxicity endpoint, we collected toxic small molecules with multiple toxicity endpoints from previous study. The dataset comprises 27 toxic endpoints categorized int...

Using transfer learning-based plant disease classification and detection for sustainable agriculture.

Subsistence farmers and global food security depend on sufficient food production, which aligns with the UN's "Zero Hunger," "Climate Action," and "Re...

Predicting extremely low body weight from 12-lead electrocardiograms using a deep neural network.

Previous studies have successfully predicted overweight status by applying deep learning to 12-lead electrocardiogram (ECG); however, models for predi...

Rewiring care delivery through Digital Therapeutics (DTx): a machine learning-enhanced assessment and development (M-LEAD) framework.

BACKGROUND: Digital transformation has sparked profound change in the healthcare sector through the development of innovative digital technologies. Di...

Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA).

Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and occurs in almost all habitable parts of the world. T...

Addressing bias in artificial intelligence for public health surveillance.

Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the time...

Artificial intelligence and machine learning algorithms in the detection of heavy metals in water and wastewater: Methodological and ethical challenges.

Heavy metals (HMs) enter waterbodies through various means, which, when exceeding a threshold limit, cause toxic effects both on the environment and i...

Toxicovigilance 2.0 - modern approaches for the hazard identification and risk assessment of toxicants in human beings: A review.

The attempt to define toxicovigilance can be based on defining its fundamental principles: prevention of infections with toxic substances, collecting ...

Optimization strategy of community planning for environmental health and public health in smart city under multi-objectives.

As population density increases, environmental hygiene and public health become increasingly severe. As the space where residents stay for the longest...

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicol...

Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more practical approach to arrhythmia detection. Using...

Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.

With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), whic...

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term ...

Molecular marker identification, antioxidant, antinociceptive, and anti-inflammatory responsiveness of malonic acid capped silver nanoparticle.

Nano-sized silver has drawn a great deal of attention in the field of health sciences owing to its remarkable therapeutic applications. Interestingly,...

A comprehensive review on artificial intelligence in water treatment for optimization. Clean water now and the future.

Given the severe effects that toxic compounds present in wastewater streams have on humans, it is imperative that water and wastewater streams polluti...

A neural network model for the evolution of learning in changing environments.

Learning from past experience is an important adaptation and theoretical models may help to understand its evolution. Many of the existing models stud...

An integrated approach on the enzymatic and antioxidant mechanisms of four commercially available essential oils ( and ) traditionally used topically for their anti-inflammatory effects.

Despite the increasing number of essential oils being reported on their potential therapeutic effects, some remain relatively unknown on their biolog...

Antimicrobial activity of nature-inspired molecules against multidrug-resistant bacteria.

Multidrug-resistant bacterial infections present a serious challenge to global health. In addition to the spread of antibiotic resistance, some bacter...

Natural deep eutectic solvents-based green extraction of vanillin: optimization, purification, and bioactivity assessment.

The sustainable extraction of natural compounds has recently attracted significant attention. The extraction of high-quality natural vanillin in activ...