AIMC Topic: Cadmium

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Rapid assessment of heavy metal accumulation capability of Sedum alfredii using hyperspectral imaging and deep learning.

Ecotoxicology and environmental safety
Hyperaccumulators are the material basis and key to the phytoremediation of heavy metal contaminated soils. Conventional methods for screening hyperaccumulators are highly dependent on the time- and labor-consuming sampling and chemical analysis. In ...

Optimal biochar selection for cadmium pollution remediation in Chinese agricultural soils via optimized machine learning.

Journal of hazardous materials
Biochar is effective in mitigating heavy metal pollution, and cadmium (Cd) is the primary pollutant in agricultural fields. However, traditional trial-and-error methods for determining the optimal biochar remediation efficiency are time-consuming and...

A machine learning model predicts stroke associated with blood cadmium level.

Scientific reports
Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental toxicant that may contribute to cardiovascular disease, including stroke. We aimed to build an effective and interpretable machine learning (ML) model...

Predicting Cd(II) adsorption capacity of biochar materials using typical machine learning models for effective remediation of aquatic environments.

The Science of the total environment
The screening and design of "green" biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Reg...

Leveraging machine learning to unravel the impact of cadmium stress on goji berry micropropagation.

PloS one
This study investigates the influence of cadmium (Cd) stress on the micropropagation of Goji Berry (Lycium barbarum L.) across three distinct genotypes (ERU, NQ1, NQ7), employing an array of machine learning (ML) algorithms, including Multilayer Perc...

Applying machine learning to construct an association model for lung cancer and environmental hormone high-risk factors and nursing assessment reconstruction.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
INTRODUCTION: To utilize machine learning techniques to develop an association model linking lung cancer and environmental hormones to enhance the understanding of potential lung cancer risk factors and refine current nursing assessments for lung can...

Development and application of machine learning models for prediction of soil available cadmium based on soil properties and climate features.

Environmental pollution (Barking, Essex : 1987)
Identifying the key influencing factors in soil available cadmium (Cd) is crucial for preventing the Cd accumulation in the food chain. However, current experimental methods and traditional prediction models for assessing available Cd are time-consum...

A novel method for multi-pollutant monitoring in water supply systems using chemical machine vision.

Environmental science and pollution research international
Drinking water is vital for human health and life, but detecting multiple contaminants in it is challenging. Traditional testing methods are both time-consuming and labor-intensive, lacking the ability to capture abrupt changes in water quality over ...

Ultra-fast whole-body bone tomoscintigraphies achieved with a high-sensitivity 360° CZT camera and a dedicated deep-learning noise reduction algorithm.

European journal of nuclear medicine and molecular imaging
UNLABELLED: This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 min, routinely provided by a high-sensitivity 360° cadmium and zinc telluride (CZT) camera, can be f...

Multitask Deep Learning Enabling a Synergy for Cadmium and Methane Mitigation with Biochar Amendments in Paddy Soils.

Environmental science & technology
Biochar has demonstrated significant promise in addressing heavy metal contamination and methane (CH) emissions in paddy soils; however, achieving a synergy between these two goals is challenging due to various variables, including the characteristic...