Public Health & Policy

Environmental Health

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

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Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG.

OBJECTIVES: Sleep apnea is the most common sleep disorder that leads to serious health complications...

Short Single-Lead ECG Signal Delineation-Based Deep Learning: Implementation in Automatic Atrial Fibrillation Identification.

Physicians manually interpret an electrocardiogram (ECG) signal morphology in routine clinical pract...

Environmentally sustainable development and use of artificial intelligence in health care.

Artificial intelligence (AI) can transform health care by delivering medical services to underserved...

A new pairwise deep learning feature for environmental microorganism image analysis.

Environmental microorganism (EM) offers a highly efficient, harmless, and low-cost solution to envir...

A CT image feature space (CTIS) loss for restoration with deep learning-based methods.

Deep learning-based methods have been widely used in medical imaging field such as detection, segmen...

Online learning-empowered smart management for AO process in sewage treatment processes.

Using artificial intelligence method to describe general working process is a more meaningful and wi...

Human health risk identification of petrochemical sites based on extreme gradient boosting.

Petrochemical industry is a key industry of soil pollution, which presents great effects on human he...

Implementation of an early warning system with hyperspectral imaging combined with deep learning model for chlorine in refuse derived fuels.

Chlorine content is one of the most important parameters in Refuse Derived Fuels (RDFs) used as a fu...

IoT-based automated water pollution treatment using machine learning classifiers.

Water is one of the most vital sources for the survival of life. In the globe, the accessibility of ...

Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning.

Microplastics quantification and classification are demanding jobs to monitor microplastic pollution...

Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling.

Dam safety assessment is important to implement the appropriate measures to avoid a dam break disast...

Recurrent Neural Network Based Link Quality Prediction for Fluctuating Low Power Wireless Links.

One of the main methods for link quality prediction is to predict the physical layer parameters firs...

Runoff Forecasting Using Machine-Learning Methods: Case Study in the Middle Reaches of Xijiang River.

Runoff forecasting is useful for flood early warning and water resource management. In this study, b...

Rapid in measurements of brown tide algae cell concentrations using fluorescence spectrometry and generalized regression neural network.

The frequent occurrence of brown tide pollution in recent years has brought great losses to the econ...

Feature Identification With a Heuristic Algorithm and an Unsupervised Machine Learning Algorithm for Prior Knowledge of Gait Events.

The purpose of this study was to compare a heuristic feature identification algorithm with output fr...

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven...

A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines.

The reformations of the electrical power sector have resulted in very dynamic and competitive market...

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