AIMC Topic: Lead

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Prediction of lead (Pb) adsorption on attapulgite clay using the feasibility of data intelligence models.

Environmental science and pollution research international
This study investigates the performance of support vector machine (SVM), multivariate adaptive regression spline (MARS), and random forest (RF) models for predicting the lead (Pb) adsorption by attapulgite clay. Models are constructed using batch sto...

Hyperspectral technique combined with deep learning algorithm for detection of compound heavy metals in lettuce.

Food chemistry
The aim of this research was to develop a deep learning method which involved wavelet transform (WT) and stack convolution auto encoder (SCAE) for extracting compound heavy metals detection deep features of lettuce leaves. WT was used to decompose th...

Multi-media biomarkers: Integrating information to improve lead exposure assessment.

Environmental research
Exposure assessment traditionally relies on biomarkers that measure chemical concentrations in individual biological media (i.e., blood, urine, etc.). However, chemicals distribute unevenly among different biological media; thus, each medium provides...

Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.

International journal of environmental research and public health
Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but their combined impact on hypercholesterolemia (HC) is poorly understood. The aim of this study was to compare the performance of various machine learning ...

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

Bulletin of environmental contamination and toxicology
Environmental pollution of aquatic ecosystems leads to an interference in several fundamental biochemical and physiological functions. In this study the interference of Cd and Pb pollutions on the physiological growth and subsequently on the age dete...

Compound washing remediation and response surface analysis of lead-contaminated soil in mining area by fermentation broth and saponin.

Environmental science and pollution research international
The development of eluent is the key to soil washing remediation, and a compound eluent was constructed using the prepared citric acid fermentation broth and saponin in this study. It displayed a good washing performance for Pb, Cu, Cr, and Cd in red...

Serum Concentrations of New Predictive Cardiovascular Disease Biomarkers in Mexican Women Exposed to Lead.

Archives of environmental contamination and toxicology
The purpose of this study was to evaluate lead exposure and its relationship with serum levels of predictive CVD biomarkers [asymmetric dimethylarginine (ADMA), adipocyte fatty acid-binding protein (FABP4), adiponectin, and chemerin] in women living ...

Analysis of the Importance of Oxides and Clays in Cd, Cr, Cu, Ni, Pb and Zn Adsorption and Retention with Regression Trees.

PloS one
This study determines the influence of the different soil components and of the cation-exchange capacity on the adsorption and retention of different heavy metals: cadmium, chromium, copper, nickel, lead and zinc. In order to do so, regression models...

Impact of robotics and a suspended lead suit on physician radiation exposure during percutaneous coronary intervention.

Cardiovascular revascularization medicine : including molecular interventions
BACKGROUND: Reports of left-sided brain malignancies among interventional cardiologists have heightened concerns regarding physician radiation exposure. This study evaluated the impact of a suspended lead suit and robotic system on physician radiatio...

Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

The international journal of neuropsychopharmacology
BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographi...