AIMC Topic: China

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Analysis of spatial heterogeneity in Xi'an's urban heat island effect using multi-source data fusion.

PloS one
In the context of global climate change, this study aims to investigate the spatial heterogeneity and driving mechanisms of the urban heat island (UHI) effect within Xi'an's second ring road area. We constructed a novel multi-source data fusion frame...

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China.

Scientific reports
This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 patients with T2DM w...

Identifying subjective life expectancy risk factors in physically active and inactive middle-aged and older adults using machine learning models.

BMC public health
BACKGROUND: Physical activity is a key focus in the field of public health, and subjective life expectancy is closely associated with individuals' physical and psychological well-being. This study aimed to identify the risk factors for subjective lif...

Hospital Outcome of Host Heterogeneity, Organ dysfunction and Trajectory in sepsis (HOHHOT): A cohort study in the critical care unit.

BMJ open
INTRODUCTION: Prognosis estimation is the basis for establishing the personal interventions in sepsis patients. Serum biomarkers are potential tools for predicting the outcomes of sepsis patients admitted to the intensive care unit (ICU). Here, we pl...

Influencing factors for childbirth readiness among pregnant women based on the reciprocal determinism theory and backpropagation neural network: a cross-sectional study in China.

BMC pregnancy and childbirth
BACKGROUND: Childbirth readiness is essential for improving maternal health outcomes and reducing mortality, yet preparedness remains low among pregnant women globally. This study aims to identify key factors influencing childbirth readiness among Ch...

Prediction model for depression risk in middle-aged and elderly patients with metabolic syndrome: a nomogram and interpretable machine learning approach based on CHARLS.

BMC psychiatry
BACKGROUND: Individuals with metabolic syndrome (MetS) are more prone to depression, which is a significant complication impacting quality of life. This research seeks to create and validate predictive models for assessing depression risk in patients...

Quantitative inversion of soil heavy metal pollution using a GA-BP neural network model.

Environmental monitoring and assessment
With the rapid development of industrialization in China, significant economic benefits have been accompanied by varying degrees of threat to the soil environment, particularly from heavy metal pollution. The rapid quantitative inversion of heavy met...

Development and validation of a machine learning-based model to predict the risk of hospitalization death in hospitalized patients with AECOPD.

Scientific reports
Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a leading cause of hospitalization and death in COPD patients. Machine learning (ML) approach is powerful but has a "black box" issue with an undirect interpretation of the ML te...

Bibliometric Insights Into the Infodemic: Global Research Trends and Policy Responses: Quantitative Research.

JMIR medical informatics
BACKGROUND: Amidst the COVID-19 pandemic, the proliferation of misinformation on social media, termed the "infodemic," has complicated global health responses.

Study on rural landscape design strategies integrating computer vision and deep learning: an analysis based on human perception and visual aesthetics.

Scientific reports
With the increasing application of artificial intelligence in environmental design, computer vision and deep learning have emerged as crucial tools for understanding human visual perception. This study focuses on rural landscapes and proposes a visua...