Public Health & Policy

Environmental Health

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

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Machine Learning-Guided Three-Dimensional Printing of Tissue Engineering Scaffolds.

Various material compositions have been successfully used in 3D printing with promising applications...

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Metals are considered to be one of the most hazardous substances due to their potential for accumula...

The in vitro toxicity evaluation of halloysite nanotubes (HNTs) in human lung cells.

Halloysite nanotubes (HNTs) have been increasingly used in many industrial and biomedical fields. Th...

Effect of silver nanospheres and nanowires on human airway smooth muscle cells: role of sulfidation.

: The toxicity of inhaled silver nanoparticles on contractile and pro-inflammatory airway smooth mus...

Accuracy, uncertainty, and interpretability assessments of ANFIS models to predict dust concentration in semi-arid regions.

Accurate prediction of the dust concentration (DC) is necessary to reduce its undesirable environmen...

Long-term PM exposure and the clinical application of machine learning for predicting incident atrial fibrillation.

Clinical impact of fine particulate matter (PM) air pollution on incident atrial fibrillation (AF) h...

Green Supplier Selection Using Fuzzy Multiple-Criteria Decision-Making Methods and Artificial Neural Networks.

In recent years, environmental awareness has increased considerably, and in order to decrease endang...

Ensemble-based deep learning for estimating PM over California with multisource big data including wildfire smoke.

INTRODUCTION: Estimating PM concentrations and their prediction uncertainties at a high spatiotempor...

Effectiveness of groundwater heavy metal pollution indices studies by deep-learning.

Globally, groundwater heavy metal (HM) pollution is a serious concern, threatening drinking water sa...

Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models.

Hybrid artificial intelligence (AI) models are developed for sediment lead (Pb) prediction in two Ba...

Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.

Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, th...

Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.

IMPORTANCE: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current pract...

Precision psychiatry in clinical practice.

The treatment of depression represents a major challenge for healthcare systems and choosing among t...

A robust soft sensor to monitor 1,3-propanediol fermentation process by Clostridium butyricum based on artificial neural network.

With the aggravation of environmental pollution and energy crisis, the sustainable microbial ferment...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effec...

The Silent Operation Theatre Optimisation System (SOTOS) to reduce noise pollution during da Vinci robot-assisted laparoscopic radical prostatectomy.

To reduce noise pollution and consequently stress during robot-assisted laparoscopic radical prostat...

Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram.

Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-lead el...

Multimodality Imaging and Artificial Intelligence for Tumor Characterization: Current Status and Future Perspective.

Research in medical imaging has yet to do to achieve precision oncology. Over the past 30 years, onl...

Optimal Selection of Sewage Treatment Technologies in Town Areas: A Coupled Multi-Criteria Decision-Making Model.

In recent years, the development of sewage treatment technologies has made many treatment options av...

A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication.

BACKGROUND: Wildland fire (wildfire; bushfire) pollution contributes to poor air quality, a risk fac...

Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture.

Smart agriculture based on new types of sensors, data analytics and automation, is an important enab...

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