Public Health & Policy

Environmental Health

Latest AI and machine learning research in environmental health for healthcare professionals.

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Deep learning for multi-year ENSO forecasts.

Variations in the El Niño/Southern Oscillation (ENSO) are associated with a wide array of regional c...

Deep learning identifies accurate burst locations in water distribution networks.

Pipe bursts in water distribution networks lead to considerable water loss and pose risks of bacteri...

Estimating daily PM concentrations in New York City at the neighborhood-scale: Implications for integrating non-regulatory measurements.

Previous PM related epidemiological studies mainly relied on data from sparse regulatory monitors to...

Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs.

BACKGROUND: Sex and age have long been known to affect the ECG. Several biologic variables and anato...

Synthesis of Electrocardiogram V-Lead Signals From Limb-Lead Measurement Using R-Peak Aligned Generative Adversarial Network.

Recently, portable electrocardiogram (ECG) hardware devices have been developed using limb-lead meas...

Accurate detection of atrial fibrillation from 12-lead ECG using deep neural network.

Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram (ECG) is...

Multi-Level Comparison of Machine Learning Classifiers and Their Performance Metrics.

Machine learning classification algorithms are widely used for the prediction and classification of ...

Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land us...

Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.

Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but thei...

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches.

Textile industry wastewaters, which cause serious problems in the environment and human health, incl...

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's larges...

A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.

Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health....

Opportunities and Challenges in Phenotypic Screening for Neurodegenerative Disease Research.

Toxic misfolded proteins potentially underly many neurodegenerative diseases, but individual targets...

Multifunctional and biodegradable self-propelled protein motors.

A diversity of self-propelled chemical motors, based on Marangoni propulsive forces, has been develo...

Solving visual pollution with deep learning: A new nexus in environmental management.

Visual pollution is a relatively new concern amidst the existing plethora of mainstream environmenta...

DeepHarmony: A deep learning approach to contrast harmonization across scanner changes.

Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibi...

Machine learning models accurately predict ozone exposure during wildfire events.

Epidemiologists use prediction models to downscale (i.e., interpolate) air pollution exposure where ...

Determination of the physical domain for air quality monitoring stations using the ANP-OWA method in GIS.

Air pollution is a major concern in some megacities of Iran. Specific cities in the country have rea...

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