Public Health & Policy

Environmental Health

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

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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 m...

Scientific novelty beyond the experiment.

Practical experiments drive important scientific discoveries in biology, but theory-based research s...

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 devel...

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...

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...

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 ...

Transformer-based deep learning method for optimizing ADMET properties of lead compounds.

A successful drug needs to exhibit both effective pharmacodynamics (PD) and safe pharmacokinetics (P...

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 envi...

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. Ho...

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

The degradation of the ecological environment caused by industrialization presents a major challenge...

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 t...

Traditional Machine and Deep Learning for Predicting Toxicity Endpoints.

Molecular structure property modeling is an increasingly important tool for predicting compounds wit...

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and...

Ultra-Low-Power E-Nose System Based on Multi-Micro-LED-Integrated, Nanostructured Gas Sensors and Deep Learning.

As interests in air quality monitoring related to environmental pollution and industrial safety incr...

TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity.

Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, w...

Structure-preserved meta-learning uniting network for improving low-dose CT quality.

Deep neural network (DNN) based methods have shown promising performances for low-dose computed tomo...

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

BACKGROUND: Air pollution epidemiology has primarily relied on measurements from fixed outdoor air q...

Machine Learning-Based Models with High Accuracy and Broad Applicability Domains for Screening PMT/vPvM Substances.

Persistent, mobile, and toxic (PMT) substances and very persistent and very mobile (vPvM) substances...

Real-time streamflow forecasting in a reservoir-regulated river basin using explainable machine learning and conceptual reservoir module.

Real-time streamflow forecasting is essential to manage water resources effectively in a reservoir-r...

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC.

The utilization of unlabeled electrocardiogram (ECG) data is always a critical topic in artificial i...

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