Environmental Health

[AI-BASED HEALTH AND BIOLOGICAL SCIENCES: AN OPPORTUNITY FOR ISRAELI LEADERSHIP].

Artificial Intelligence (AI) has become a key tool for the acceleration of scientific discovery, fro...

Enhancing Asthma Self-Management with Environmental Passive-Monitoring Data and Machine Learning-Based Predictions.

Monitoring enables timely action which is critical in avoiding asthma attacks. With the abundance of...

[Soil Cadmium Prediction and Health Risk Assessment of an Oasis on the Eastern Edge of the Tarim Basin Based on Feature Optimization and Machine Learning].

Soil heavy metal pollution poses a serious threat to food security, human health, and soil ecosystem...

Generating, modeling and evaluating a large-scale set of CRISPR/Cas9 off-target sites with bulges.

The CRISPR/Cas9 system is a highly accurate gene-editing technique, but it can also lead to unintend...

Electrocardiographic Classification using Deep Learning with Lead Switching.

The classification algorithms of rhythm and morphology abnormalities in electrocardiogram (ECG) sign...

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected ar...

Machine Learning-Based Prediction of Hospitalization During Chemoradiotherapy With Daily Step Counts.

IMPORTANCE: Toxic effects of concurrent chemoradiotherapy (CRT) can cause treatment interruptions an...

[A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis].

Pneumoconiosis ranks first among the newly-emerged occupational diseases reported annually in China,...

Rapid fiber-detection technique by artificial intelligence in phase-contrast microscope images of simulated atmospheric samples.

Since the manufacture, import, and use of asbestos products have been completely abolished in Japan,...

AI can help to tailor drugs for Africa - but Africans should lead the way.

Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals.

Green toxicology is marching chemistry into the 21st century. This emerging framework will transform...

Deep learning-derived 12-lead electrocardiogram-based genotype prediction for hypertrophic cardiomyopathy: a pilot study.

Given the psychosocial and ethical burden, patients with hypertrophic cardiomyopathy (HCMs) could b...

A graph-based modeling framework for tracing hydrological pollutant transport in surface waters.

Anthropogenic pollution of hydrological systems affects diverse communities and ecosystems around th...

How AI could lead to a better understanding of the brain.

Deep learning based an effective hybrid model for water quality assessment.

Water, which is very important for life and civilizations on Earth, has been a source of life for al...

QTNet: Deep Learning for Estimating QT Intervals Using a Single Lead ECG.

QT prolongation often leads to fatal arrhythmia and sudden cardiac death. Antiarrhythmic drugs can i...

Gated CNN-Transformer Network for Automatic Cardiovascular Diagnosis using 12-lead Electrocardiogram.

12-lead electrocardiogram (ECG) is a widely used method in the diagnosis of cardiovascular disease (...

[A method for photoplethysmography signal quality assessment fusing multi-class features with multi-scale series information].

Photoplethysmography (PPG) is often affected by interference, which could lead to incorrect judgment...

Validation of wastewater data using artificial intelligence tools and the evaluation of their performance regarding annotator agreement.

To prevent the pollution of water resources, the measurement and the limitation of wastewater discha...

Benchmarking the Impact of Noise on Deep Learning-Based Classification of Atrial Fibrillation in 12-Lead ECG.

Electrocardiography analysis is widely used in various clinical applications and Deep Learning model...

TRSRD: a database for research on risky substances in tea using natural language processing and knowledge graph-based techniques.

During the production and processing of tea, harmful substances are often introduced. However, they ...