Public Health & Policy

Environmental Health

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

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First Case Report Of Anca-Associated Vasculitis And Anthracosis Coexistence.

Anthracosis is a type of mild pneumoconiosis secondary to harmless carbon dust deposits. Although an...

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, t...

Automatic arrhythmia detection with multi-lead ECG signals based on heterogeneous graph attention networks.

Automatic arrhythmia detection is very important for cardiovascular health. It is generally performe...

Improving Deep Learning-based Cardiac Abnormality Detection in 12-Lead ECG with Data Augmentation.

Automated Electrocardiogram (ECG) classification using deep neural networks requires large datasets ...

Next-generation 5G fusion-based intelligent health-monitoring platform for ethylene cracking furnace tube.

This study aimed to develop a 5G + "mixed computing" + deep learning-based next-generation intellige...

[Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network].

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk class...

Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems.

Urbanization and an increase in precipitation intensities due to climate change, in addition to limi...

Digital Healthcare for Airway Diseases from Personal Environmental Exposure.

Digital technologies have emerged in various dimensions of human life, ranging from education to pro...

A Clinician's Guide to Artificial Intelligence (AI): Why and How Primary Care Should Lead the Health Care AI Revolution.

Artificial intelligence (AI) in health care is the future that is already here. Despite its potentia...

Artificial Intelligence in Compound Design.

Artificial intelligence has seen an incredibly fast development in recent years. Many novel technolo...

Machine learning-driven identification of early-life air toxic combinations associated with childhood asthma outcomes.

Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that ca...

Signal Quality Assessment of PPG Signals using STFT Time-Frequency Spectra and Deep Learning Approaches.

Photoplethysmography (PPG) is an important signal which contains much physiological information like...

Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms.

Low-cost wearables with capability to record electrocardiograms (ECG) are becoming increasingly avai...

Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.

IMPORTANCE: Millions of clinicians rely daily on automated preliminary electrocardiogram (ECG) inter...

Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations.

The real-time monitoring of reductions of economic activity by containment measures and its effect o...

Deep Learning for Automated Diabetic Retinopathy Screening Fused With Heterogeneous Data From EHRs Can Lead to Earlier Referral Decisions.

PURPOSE: Fundus images are typically used as the sole training input for automated diabetic retinopa...

CyanoPATH: a knowledgebase of genome-scale functional repertoire for toxic cyanobacterial blooms.

CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyano...

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