AIMC Topic: China

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Evaluation of landslide susceptibility based on SMOTE-Tomek sampling and machine learning algorithm.

PloS one
Landslides are frequent and hazardous geological disasters, posing significant risks to human safety and infrastructure. Accurate assessments of landslide susceptibility are crucial for risk management and mitigation. However, geological surveys of l...

Machine Learning Models to Identify Clinically Significant Anxiety in Short-Term Insomnia Using Accelerometers.

Depression and anxiety
Clinically significant anxiety (CSA) is common in individuals with short-term insomnia. This study aims to explore the relationship between CSA and the subjective and objective parameters of sleep in patients with short-term insomnia and construct ma...

Zipf's law in China's local government work reports: A 21-year study using natural language processing and regression analysis.

PloS one
The examination and application of Zipf's law is a significant topic in quantitative linguistics. This study presents an in-depth empirical investigation of this law in 651 Chinese provincial government work reports (2003-2023). Employing natural lan...

How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China.

PloS one
Natural landscapes are crucial resources for enhancing visitor experiences in ecotourism destinations. Previous research indicates that high temperatures may impact tourists' perception of landscapes and emotions. Still, the potential value of natura...

Landslide susceptibility mapping using an entropy index-based negative sample selection strategy: A case study of Luolong county.

PloS one
Landslides constitute a significant geological hazard in China, particularly in high-altitude regions like the Himalayas, where the challenging environmental conditions impede field surveys. This research utilizes the IOE model to refine non-landslid...

Can the Use of Artificial Intelligence-Generated Content Bridge the Cancer Knowledge Gap? A Longitudinal Study With Health Self-Efficacy as a Mediator and Educational Level as a Moderator.

Cancer control : journal of the Moffitt Cancer Center
OBJECTIVES: The cancer knowledge gap represents a significant disparity in awareness and understanding of cancer-related information across different demographic groups. Leveraging Artificial Intelligence-Generated Content (AIGC) offers a promising a...

Identifying protected health information by transformers-based deep learning approach in Chinese medical text.

Health informatics journal
In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for pri...

Clinical Application of a Big Data Machine Learning Analysis Model for Osteoporotic Fracture Risk Assessment Built on Multicenter Clinical Data in Qingdao City.

Discovery medicine
BACKGROUND: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, there is a lack of comprehensive and validated risk assessment models for OPF. This study aims to develo...

Machine learning-enabled risk prediction of self-neglect among community-dwelling older adults in China.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Elder self-neglect (ESN) is usually ignored as a private problem and impairs the health outcomes of older adults. It is essential to construct a robust and efficient tool for risk prediction which can better detect and prevent self-neglec...

Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.

Environmental health and preventive medicine
BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiovascular diseases, affecting vital organs such as the heart, brain, and kidneys. Our goal is to predict the risk of new onset hypertension using machin...