Environmental Health

Causal inference in health services research: concepts, methods and application perspectives.

Health services research faces the challenge of providing sound recommendations for action for the further development of health systems and care. The application of causal inference methods offers health services researchers an excellent opportunity to identify causal relationships under everyday conditions. The role of clinical trials with a classic randomised controlled trial (RCT) design is re...

Data-Driven Approach toward the Quantification of Gases in a Complex Mixture Using a Non-Selective Single Metal Oxide Gas Sensor.

Detection of trace levels of volatile organic compounds (VOCs) has widespread applications, including wearable diagnostics, IoTs, and indoor air quality control. Although metal oxide semiconductors (MOS) arguably offer the best sensitivity for a wide range of VOCs, their poor selectivity limits their performance. Here, we demonstrate a machine learning (ML)-based analysis and framework using a sin...

Climate driven drought risk and machine learning approaches for urban resilience and sustainable water governance.

Drought is thought of as one of the gravest climate-related hazards of the agro-dependent regions facing water stress like Pakistan where socio-econom...

TabulaTime: Novel multimodal deep learning for Acute Coronary Syndrome prediction through environmental and clinical data integration.

Acute Coronary Syndromes (ACS), including ST- and non-ST-segment elevation myocardial infarction (STEMI, NSTEMI), remain a leading cause of global mor...

Impact of corrosive groundwater on water infrastructure and public health in the contiguous United States.

In U.S. drinking water systems, corrosion in aging iron (Fe) and lead (Pb) pipes imposes significant economic challenges, damages infrastructure, and ...

A novel polymer-sensitive index coupled with multivariate and machine learning modeling for microplastic risk assessment in coastal sediments of the bay of Bengal.

Microplastic (MP) contamination in coastal sediments poses growing ecological and human health concerns, yet data for developing nations remain limite...

Resilience-by-design in engineering Bacillus cell factories.

Industrial Bacillus strains face overlapping stresses-heat, pH, oxidative, osmotic, and toxic metabolites-during large-scale fermentation. Traditional...

The essential role of methylation in maize (Zea mays) defense against the seed-colonizing fungus Aspergillus flavus.

UNLABELLED: The interaction between maize (Zea mays) and Aspergillus species poses a huge threat to global food safety due to the production of aflato...

Environmental education as a means of combating growing environmental pollution: an optimized- explainable artificial intelligence (XAI) approach.

This work aimed at the use and understanding the impact of education in solving the growing environmental pollution and radiation exposure, which are ...

Modeling community hydrogen sulfide exposure in an urban industrial area during routine and extreme events.

Hydrogen sulfide (H2S) is a toxic, odorous gas linked to acute and chronic health effects. In urban-industrial areas like Southern California's South ...

Integrating target, nontarget analysis with machine learning to illuminate PFAS characteristics and health risks in Chinese cosmetics.

Per- and polyfluoroalkyl substances (PFAS) are extensively incorporated into cosmetics to enhance durability and water resistance. However, their perv...

Harnessing bacterial power and omics technologies for sustainable plastic waste biodegradation.

Plastic pollution constitutes a critical environmental concern of this era, with synthetic polymers, i.e., polyethylene (PE), polyethylene terephthala...

6PPD-quinone promotes ovarian cancer progression: Insights from network toxicology, machine learning, and in vitro validation.

6PPD-quinone (6PPD-Q), a toxic tire-derived antioxidant transformation product, is a pervasive environmental contaminant linked to reproductive toxici...

Prediction of groundwater total nitrogen via an interpretable ensemble machine learning framework: Implications for groundwater diversion management in complex catchments.

Groundwater total nitrogen (TN) is a key indicator of groundwater ecological security, and accurate prediction and driver identification are essential...

PM2.5 exposure induces functional alterations in pregnant rats heart and in human stem cell derived cardiac spheroids.

Air pollution is a major cardiovascular risk factor, with particulate matter (PM) posing significant threats. The Po Valley remains among Europe's mos...

An integrated water quality assessment and its prediction utilizing the CWQI, CRITIC based-improved CWQI, sensitivity analysis, multivariate techniques, machine learning algorithms and GIS approaches to determine pollution intensities in the river basin (Odisha).

The Mahanadi River is a vital water resource for the Odisha region, supporting both local agriculture and drinking water needs. However, increasing hu...

Interpretable machine learning assisted optimization of antimony adsorption by metal-organic frameworks: combined with characterization methods for adsorption mechanism analysis.

Antimony (Sb) contamination in aquatic environments poses serious risks to human health and ecosystem integrity. Conventional remediation techniques f...

Highly sensitive superhydrophobic SERS substrate combined with machine learning for precise identification and classification of nanoplastics.

The ubiquitous use of plastics in modern society is accompanied by the pervasive occurrence of plastic pollution. Of particular concern are nanoplasti...

NeuroCardioSense (NCS): A Time-Aware Fuzzy Decision Framework for Multi-Lead ECG Classification and Arrhythmia Detection.

Accurate classification of electrocardiogram (ECG) signals is essential for automated arrhythmia detection and clinical decision support. Existing dee...

Harnessing machine learning to explore influencing mechanism in the dual pro-environmental intention-behavior gap.

Fostering pro-environmental behaviors (PEBs) is crucial for advancing low-carbon development. A significant obstacle in this endeavor is the intention...