AIMC Topic: China

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Chinese medical named entity recognition based on multimodal information fusion and hybrid attention mechanism.

PloS one
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...

The concise machine learning prediction models for suicide attempt in China: Based on demographic and social factors.

Journal of affective disorders
BACKGROUND: Recently, the machine learning (ML) methods have been recommended to predict suicide attempts (SA). However, there is little literature reported the prediction models based on multiple machine learning methods of Chinese people and previo...

Decoding PM oxidative potential in Ningbo, China: Key chemicals, sources, and health risks via dual-assay and machine learning.

Journal of hazardous materials
PM oxidative potential (OP), a key driver of health risks, was investigated in Ningbo, China, using dual dithiothreitol (DTT) and ascorbic acid (AA) assays combined with machine learning (ML). This approach accounts for the complexity of interactions...

Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example.

Environment international
Continuous Emission Monitoring Systems (CEMS) are critical for real-time pollutant measurement, widely deployed to supervise industrial emissions and ensure regulatory compliance. Despite their utility, CEMS data face challenges of data fabrications,...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

BMC medical informatics and decision making
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 ...

Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China.

Ecotoxicology and environmental safety
Soil heavy metal contamination poses serious health risks, but few studies have quantitatively assessed disparities in these risks between urban and rural populations. To address this gap, we introduce a novel framework integrating machine learning a...

Long-term exposure to PM and liver cancer mortality: Insights into the role of smaller particulate fractions.

Ecotoxicology and environmental safety
Particulate matter (PM) is a recognized carcinogen, but the effects of PM on liver cancer remain underexplored. This study investigates the long-term association between PM and liver cancer mortality, as well as the contribution of smaller particles ...

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
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
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.