Environmental Health

Coupling ANFIS with ant colony optimization (ACO) algorithm for 1-, 2-, and 3-days ahead forecasting of daily streamflow, a case study in Poland.

Finding an efficient and reliable streamflow forecasting model has always been an important challenge for managers and planners of freshwater resources. The current study, based on an adaptive neuro-fuzzy inference system (ANFIS) model, was designed to predict the Warta river (Poland) streamflow for 1 day, 2 days, and 3 days ahead for a data set from the period of 1993-2013. The ANFIS was addition...

Deep Learning-Based Road Traffic Noise Annoyance Assessment.

With the development of urban road traffic, road noise pollution is becoming a public concern. Controlling and reducing the harm caused by traffic noise pollution have been the hot spots of traffic noise management research. The subjective annoyance level of traffic noise has become one of the most important measurements for evaluating road traffic pollution. There are subjective experimental meth...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increase...

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review.

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artifici...

Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods.

The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic lev...

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortalit...

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an ...

PM2.5 Concentration Prediction Model: A CNN-RF Ensemble Framework.

Although many machine learning methods have been widely used to predict PM2.5 concentrations, these single or hybrid methods still have some shortcomi...

3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads.

The objective of this study is to explore new imaging techniques with the use of the deep learning method for the identification of cardiac abnormalit...

Scientific novelty beyond the experiment.

Practical experiments drive important scientific discoveries in biology, but theory-based research studies also contribute novel-sometimes paradigm-ch...

Machine Learning Advances in Predicting Peptide/Protein-Protein Interactions Based on Sequence Information for Lead Peptides Discovery.

Peptides have shown increasing advantages and significant clinical value in drug discovery and development. With the development of high-throughput te...

Quantitative Prediction of Inorganic Nanomaterial Cellular Toxicity via Machine Learning.

Organic chemistry has seen colossal progress due to machine learning (ML). However, the translation of artificial intelligence (AI) into materials sci...

The ecological discourse analysis of news discourse based on deep learning from the perspective of ecological philosophy.

Recently, ecological damage and environmental pollution have become increasingly serious. Experts in various fields have started to study related issu...

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network.

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and imp...

Analysis of YOLOv5 and DeepLabv3+ Algorithms for Detecting Illegal Cultivation on Public Land: A Case Study of a Riverside in Korea.

Rivers are generally classified as either national or local rivers. Large-scale national rivers are maintained through systematic maintenance and mana...

Deep learning for detecting macroplastic litter in water bodies: A review.

Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems....

Development of a Wearable Ultrasound Transducer for Sensing Muscle Activities in Assistive Robotics Applications.

Robotic prostheses and powered exoskeletons are novel assistive robotic devices for modern medicine. Muscle activity sensing plays an important role i...

A hybrid deep learning model for regional O and NO concentrations prediction based on spatiotemporal dependencies in air quality monitoring network.

Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full u...

Air pollution, water pollution, and robots: Is technology the panacea.

The degradation of the ecological environment caused by industrialization presents a major challenge for policymakers as they aim to develop sustainab...

Assessing machine learning approaches for predicting failures of investigational drug candidates during clinical trials.

One of the major challenges in drug development is having acceptable levels of efficacy and safety throughout all the phases of clinical trials follow...