Environmental Health

The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction.

We estimate the causal effects of acute fine particulate matter exposure on mortality, health care u...

Prognostic models will be victims of their own success, unless….

Predictive analytics have begun to change the workflows of healthcare by giving insight into our fut...

Deep reinforcement learning based valve scheduling for pollution isolation in water distribution network.

Public water supply facilities are vulnerable to intentional intrusion. In particular, Water Distrib...

Will China lead the world in AI by 2030?

Myocardial Infarction Detection Based on Multi-lead Ensemble Neural Network.

Automatic myocardial infarction (MI) detection using an electrocardiogram (ECG) is of great signific...

Predicting culturable enterococci exceedances at Escambron Beach, San Juan, Puerto Rico using satellite remote sensing and artificial neural networks.

Predicting recreational water quality is key to protecting public health from exposure to wastewater...

Current status and future perspective of computational toxicology in drug safety assessment under ontological intellection.

For the safety assessment of pharmaceuticals, initial data management requires accurate toxicologica...

Platelet mitochondrial cytochrome c oxidase subunit I variants with benzene poisoning.

BACKGROUND: Chronic benzene poisoning (CBP) is one of the most common chronic occupational poisoning...

ARIADNA: machine learning method for ancient DNA variant discovery.

Ancient DNA (aDNA) studies often rely on standard methods of mutation calling, optimized for high-qu...

Atrial Fibrillation Detection in Short Single Lead ECG Recordings Using Wavelet Transform and Artificial Neural Networks.

Atrial fibrillation (AF) is a common health issue, not only in developed countries but also in devel...

[Nondestructive detection of total nitrogen content in leaves of Santalum album based on ST-PCA-BP neural network.].

Nitrogen is one of the most important elements for plant growth. Producers often use a lot of nitrog...

COMPARISON OF CARDIAC ARRHYTHMIA TYPES BETWEEN HYPERTHYROID PATIENTS WITH GRAVES' DISEASE AND TOXIC NODULAR GOITER.

PURPOSE: Previous studies have demonstrated the relationship between hyperthyroidism and increased r...

Application of Fuzzy Set/Qualitative Comparative Analysis to Public Participation Projects in Support of the EU Water Framework Directive.

  This study analyzes the level of satisfaction of stakeholders in the public participation process ...

In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method.

The cytochrome P450 (CYP) enzyme superfamily is involved in phase I metabolism which chemically modi...

Prediction of biochemical oxygen demand at the upstream catchment of a reservoir using adaptive neuro fuzzy inference system.

The aim of this study is to examine the potential of adaptive neuro fuzzy inference system (ANFIS) t...

[Toxicity of vehicle exhaust on BEAS-2B cells in vitro by air-liquid interface].

OBJECTIVE: To evaluate the toxic effect of vehicle exhaust( VE) on lung epithelial cells by air-liqu...

Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic a...

Predictions of Diffuse Pollution by the HSPF Model and the Back-Propagation Neural Network Model.

  Watershed models are important tools for predicting the possible change of watershed responses. En...

[Applications of eco-environmental big data: Progress and prospect].

With the advance of internet and wireless communication technology, the fields of ecology and enviro...

Study on Recognition of Cooking Oil Fume by Fourier Transform Infrared Spectroscopy Based on Artificial Neural Network.

With the developing of catering trade, cooking oil fume has became one of the three major air pollut...

An artificial neural network prediction model of congenital heart disease based on risk factors: A hospital-based case-control study.

An artificial neural network (ANN) model was developed to predict the risks of congenital heart dise...