AIMC Topic: China
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An integrated IKOA-CNN-BiGRU-Attention framework with SHAP explainability for high-precision debris flow hazard prediction in the Nujiang river basin, China.
PloS one
Jun 24, 2025
Debris flows represent a persistent challenge for disaster prediction in mountainous regions due to their highly nonlinear and multivariate triggering mechanisms. This study proposes an explainable deep learning framework, the Improved Kepler Optimiz...
Rockburst grade evaluation and parameter sensitivity analysis based on SSA-PNN framework: Considering rock mass strength.
PloS one
Jun 24, 2025
The occurrence of rockburst is closely related to the strength and stress conditions of rock mass. The Lalin Railway tunnel in China was taken as an example, the strength and stress parameters of rock mass at 22 rockburst locations were obtained by u...
Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.
JMIR public health and surveillance
Jun 18, 2025
BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological patterns, particularly given the impact of vaccination and recent nonpharmacological interventions.
Does the registration system reform reduce the finance sector's risk spillover effect in China's stock market-Causal inference based on dual machine learning.
PloS one
Jun 18, 2025
With growing uncertainty in global trade, improving access to domestic capital markets has become an important way to manage financial risk spillovers. This study examines how the registration system reform affects the finance sector's risk spillover...
Chinese medical named entity recognition based on multimodal information fusion and hybrid attention mechanism.
PloS one
Jun 11, 2025
Chinese Medical Named Entity Recognition (CMNER) seeks to identify and extract medical entities from unstructured medical texts. Existing methods often depend on single-modality representations and fail to fully exploit the complementary nature of di...
Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.
BMC medical informatics and decision making
Jun 6, 2025
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...
A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models.
BMC medical informatics and decision making
Jun 5, 2025
BACKGROUND AND OBJECTIVE: The machine learning (ML) models for acute myocardial infarction (AMI) are considered to have better predictive ability for mortality compared to conventional risk scoring models. However, previous ML prediction models have ...
Machine learning-based prediction model for cognitive impairment risk in patients with chronic kidney disease.
PloS one
Jun 5, 2025
BACKGROUND: The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.
Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning.
Environmental science & technology
Jun 4, 2025
Understanding aerosol vertical distribution is crucial for aerosol pollution mitigation but is hindered by limited observational data. This study employed multiaxis differential optical absorption spectroscopy (MAX-DOAS) technology with a coupled rad...
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.
Journal of health, population, and nutrition
Jun 4, 2025
BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM i...
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