BACKGROUND: The pine wood nematode (PWN) has caused tremendous damage to pine forests in China. Accurately predicting the infestation stage of PWN is crucial for implementing appropriate management, such as chemically controlling early-infested trees...
In marine environments, the sources of organophosphate esters (OPEs), particularly emerging OPEs (eOPEs) remain primarily unclear and present significant challenges for accurate source tracing. Here, we developed an unsupervised machine learning fram...
A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distribution from space is crucial for marine environmental governance. This study focuses on the Pearl River ...
BJOG : an international journal of obstetrics and gynaecology
Sep 1, 2025
OBJECTIVE: To create and validate a machine learning (ML)-based model for predicting the adverse perinatal outcome (APO) in foetal growth restriction (FGR) at diagnosis.
International journal of legal medicine
Sep 1, 2025
The epiphyses of the hand and wrist serve as crucial indicators for assessing skeletal maturity in adolescents. This study aimed to develop a deep learning (DL) model for bone age (BA) assessment using hand and wrist X-ray images, addressing the chal...
BackgroundThe rapid advancement of Artificial Intelligence (AI) is driving transformative changes across various sectors, reshaping organizational management models and altering work dynamics for employees.ObjectiveThis study employs the framework of...
Preterm birth (PTB) is a primary cause of mortality among newborns globally. Prenatal exposure to environmental pollutants has been suggested to increase the PTB risk. Studies have shown NEOs may be linked to adverse birth outcomes. However, the impa...
Journal of environmental sciences (China)
Sep 1, 2025
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to i...
Understanding the response of PM-bound toxic components to source variations under climate change is crucial for public health protection. However, the lack of long-term and multi-site observational data of toxic components limits such efforts. Here,...
Contamination of cultivated soils with potentially toxic elements (PTEs) poses a growing threat to global food security. Although existing risk assessments have examined the accumulation and toxicity of PTEs, their dynamic interplay with multidimensi...
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