Environmental Health

Enhancing PM Prediction Using NARX-Based Combined CNN and LSTM Hybrid Model.

In a world where humanity's interests come first, the environment is flooded with pollutants produced by humans' urgent need for expansion. Air pollution and climate change are side effects of humans' inconsiderate intervention. Particulate matter of 2.5 µm diameter (PM) infiltrates lungs and hearts, causing many respiratory system diseases. Innovation in air pollution prediction is a must to prot...

Artificial Intelligence and Machine Learning for Lead-to-Candidate Decision-Making and Beyond.

The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research and development has to date focused on research: target identification; docking-, fragment-, and motif-based generation of compound libraries; modeling of synthesis feasibility; rank-ordering likely hits according to structural and chemometric similarity to compounds having known activity and affinity to t...

Critical features identification for chemical chronic toxicity based on mechanistic forecast models.

Facing billions of tons of pollutants entering the ocean each year, aquatic toxicity is becoming a crucial endpoint for evaluating chemical adverse ef...

Deep Learning Algorithm-Based Magnetic Resonance Imaging Feature-Guided Serum Bile Acid Profile and Perinatal Outcomes in Intrahepatic Cholestasis of Pregnancy.

This study was aimed to explore magnetic resonance imaging (MRI) based on deep learning belief network model in evaluating serum bile acid profile and...

Feature selection for global tropospheric ozone prediction based on the BO-XGBoost-RFE algorithm.

Ozone is one of the most important air pollutants, with significant impacts on human health, regional air quality and ecosystems. In this study, we us...

International Criminal Law Protection of Environmental Rights and Sentencing Based on Artificial Intelligence.

Environmental problem is an international problem that transcends national boundaries and develops into regional and global environmental pollution an...

Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell-based drug cardiotoxicity testing.

Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analysis and machine learning we can create novel tools...

Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data.

Classifying the state of the atmosphere into a finite number of large-scale circulation regimes is a popular way of investigating teleconnections, the...

An air quality index prediction model based on CNN-ILSTM.

Air quality index (AQI) is an essential measure of air pollution evaluation, which describes the air pollution degree and its impact on health, so the...

Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model.

Recently, heavy metal air pollution has received significant interest in computing the total concentration of every toxic metal. Chemical fractionatio...

Bench to bedside: The ambitious goal of transducing medicinal chemistry from the lab to the clinic.

This paper deals with a critical examination on the possibility of quantitatively predicting the in vivo activity of new chemical entities (NCEs) by m...

Reversing radiation-induced immunosuppression using a new therapeutic modality.

Radiation-induced immune suppression poses significant health challenges for millions of patients undergoing cancer chemotherapy and radiotherapy trea...

Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation.

It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the worl...

An integrated 3D CNN-GRU deep learning method for short-term prediction of PM2.5 concentration in urban environment.

This study proposes a new model for the spatiotemporal prediction of PM concentration at hourly and daily time intervals. It has been constructed on a...

A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management.

Energy is the source of economic growth, and energy consumption indicates the country's state of development. Energy engineering is a relatively new t...

Design of Sports Event Evaluation and Classification Method Based on Deep Neural Network.

Large-scale sports events with high-level competition as the main content will have a great impact on the host city whether from the economic level or...

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

It was to explore the application value of health cloud service platform based on data mining algorithm and wireless network in the analysis of psycho...

A Model Study on Raw Material Chemical Composition to Predict Sinter Quality Based on GA-RNN.

The quality control process for sintered ore is cumbersome and time- and money-consuming. When the assay results come out and the ratios are found to ...

Change in task conditions leads to changes in intermittency in intermittent feedback control employed by CNS in control of human stance.

Event-driven intermittent feedback control is a form of feedback control in which the corrective control action is only initiated intermittently when ...

Formulating Convolutional Neural Network for mapping total aquifer vulnerability to pollution.

Aquifer vulnerability mapping to pollution is topical research activity, and common frameworks such as the basic DRASTIC framework (BDF) suffer from t...