Public Health & Policy

Environmental Health

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

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An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.

Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water ...

A deep-learning method for generating synthetic kV-CT and improving tumor segmentation for helical tomotherapy of nasopharyngeal carcinoma.

Megavoltage computed tomography (MV-CT) is used for setup verification and adaptive radiotherapy in ...

Study on the use of standard 12-lead ECG data for rhythm-type ECG classification problems.

BACKGROUND AND OBJECTIVES: Most deep-learning-related methodologies for electrocardiogram (ECG) clas...

Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms.

Plants and associated microorganisms are essential sources of natural products against human cancer ...

Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction.

A wide range of applications based on sequential data, named time series, have become increasingly p...

Optimal ECG-lead selection increases generalizability of deep learning on ECG abnormality classification.

Deep learning (DL) has achieved promising performance in detecting common abnormalities from the 12-...

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular hea...

Rapid and sensitive UHPLC-MS/MS methods for dietary sample analysis of 43 mycotoxins in China total diet study.

INTRODUCTION: Mycotoxins are toxic metabolites produced by fungi that commonly contaminate foods. As...

Tool Condition Monitoring of the Cutting Capability of a Turning Tool Based on Thermography.

In turning, the wear control of a cutting tool benefits product quality enhancement, tool-related co...

Anomaly Detection of Water Level Using Deep Autoencoder.

Anomaly detection is one of the crucial tasks in daily infrastructure operations as it can prevent m...

Anti- in vitro effect of -cyclohexyl-1,2,4-oxadiazole and its ADME/TOX parameters.

Leishmaniasis is a disease that represents a serious global health problem with a potentially fatal ...

Detection of heavy metal lead in lettuce leaves based on fluorescence hyperspectral technology combined with deep learning algorithm.

The feasibility analysis of fluorescence hyperspectral imaging technology was studied for the detect...

Real-time frequency-independent single-Lead and single-beat myocardial infarction detection.

This study proposes a novel real-time frequency-independent myocardial infarction detector for Lead ...

Edge AI-Based Automated Detection and Classification of Road Anomalies in VANET Using Deep Learning.

Road surface defects are crucial problems for safe and smooth traffic flow. Due to climate changes, ...

Air quality prediction using CNN+LSTM-based hybrid deep learning architecture.

Air pollution prediction based on variables in environmental monitoring data gains further importanc...

An Approach for Thoracic Syndrome Classification with Convolutional Neural Networks.

There have been remarkable changes in our lives and the way we perceive the world with advances in c...

Evaluation of green lean production in textile industry: a hybrid fuzzy decision-making framework.

Textile industry is an old and effective industry in Iran. However, due to its age and high energy c...

Biocidal activity of Ba-doped CeO NPs against and bacterial strains.

Mishandling of antibiotics often leads to the development of multiple drug resistance (MDR) among mi...

Estimating PM concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, China.

With rapid economic growth, urbanization and industrialization, fine particulate matter with aerodyn...

Identification of Autistic Risk Candidate Genes and Toxic Chemicals via Multilabel Learning.

As a group of complex neurodevelopmental disorders, autism spectrum disorder (ASD) has been reported...

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