Environmental Health

Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

OBJECTIVE: Use of wearable ECG devices for arrhythmia screening is limited due to poor signal quality, small number of leads and short records, leading to incorrect recognition of pathological events. This paper introduces a novel approach to classification (normal/'N', atrial fibrillation/'A', other/'O', and noisy/'P') of short single-lead ECGs recorded by wearable devices.

How Specific Abilities Might Throw '' a Curve: An Idea on How to Capitalize on the Predictive Validity of Specific Cognitive Abilities.

School grades are still used by universities and employers for selection purposes. Thus, identifying determinants of school grades is important. Broadly, two predictor categories can be differentiated from an individual difference perspective: cognitive abilities and personality traits. Over time, evidence accumulated supporting the notion of the -factor as the best single predictor of school grad...

Light-Driven Micro/Nanomotor for Promising Biomedical Tools: Principle, Challenge, and Prospect.

A micro/nanomotor (MNM), as miniaturized machinery, can potentially bridge the application gap between the traditional macroscale motor and the molecu...

Robot-guided pediatric stereoelectroencephalography: single-institution experience.

OBJECTIVEStereoelectroencephalography (SEEG) has increased in popularity for localization of epileptogenic zones in drug-resistant epilepsy because sa...

Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images.

The majority of computational methods for predicting toxicity of chemicals are typically based on "nonmechanistic" cheminformatics solutions, relying ...

Identification of lead anti-human cytomegalovirus compounds targeting MAP4K4 via machine learning analysis of kinase inhibitor screening data.

Chemogenomic approaches involving highly annotated compound sets and cell based high throughput screening are emerging as a means to identify novel dr...

Effect of Cd and Pb Pollutions on Physiological Growth: Wavelet Neural Network (WNN) as a New Approach on Age Determination of Coenobita scaevola.

Environmental pollution of aquatic ecosystems leads to an interference in several fundamental biochemical and physiological functions. In this study t...

A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination.

This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysi...

Optimization and modeling of methyl orange adsorption onto polyaniline nano-adsorbent through response surface methodology and differential evolution embedded neural network.

Presence of pigments and dyes in water bodies are growing tremendously and pose as toxic materials and have severe health effects on human and aquatic...

A novel application of deep learning for single-lead ECG classification.

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach bas...

Forecasting air quality time series using deep learning.

UNLABELLED: This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality manag...

Tracking antibiotic resistance gene pollution from different sources using machine-learning classification.

BACKGROUND: Antimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in a...

Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM in the Northeastern USA.

Satellite-derived estimates of aerosol optical depth (AOD) are key predictors in particulate air pollution models. The multi-step retrieval algorithms...

Mechanism & inhibition kinetics of bioassay-guided fractions of Indian medicinal plants and foods as ACE inhibitors.

Hypertension is a becoming a major threat to the world. Angiotensin converting enzyme (ACE) is a key part in the renin angiotensin aldosterone system ...

Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a con...

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study,...

Integrating river hydromorphology and water quality into ecological status modelling by artificial neural networks.

The aim of the study was to develop predictive models of the ecological status of rivers by using artificial neural networks. The relationships betwee...

Evaluation of a novel automated water analyzer for continuous monitoring of toxicity and chemical parameters in municipal water supply.

A novel tool, the DAMTA analyzer (Device for Analytical Monitoring and Toxicity Assessment), designed for fully automated toxicity measurements based ...

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the mode...

Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity.

Primaquine (PQ) is a commonly used drug that can prevent the transmission of Plasmodium falciparum malaria, however toxicity limits its use. We prepar...