AIMC Topic: China

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Construction of a predictive model for the risk of moderate-to-severe cancer-related fatigue in colorectal cancer chemotherapy patients: an interpretable machine learning approach.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to analyze the influencing factors of moderate-to-severe cancer-related fatigue (CRF) in colorectal cancer (CRC) chemotherapy patients and to develop a predictive risk stratification model.

Water resource assessment in data-scarce hydrological regions based on limited underwater survey points.

Environmental monitoring and assessment
Lake topography, which serves as a crucial basis for water resource monitoring, has been extensively applied in hydrological and geomorphological research. However, monitoring lake dynamics in data-scarce regions remains challenging due to the limite...

Mapping the Evolution of China's Traditional Chinese Medicine Education Policies: Insights From a BERTopic-Based Descriptive Study.

JMIR medical education
BACKGROUND: Traditional Chinese medicine (TCM) education in China has evolved significantly, shaped by both national policy and social needs. Despite this, the academic community has yet to fully explore the long-term trends and core issues in TCM ed...

Measurement model of credit risk for unlisted agricultural enterprises.

PloS one
This paper aims to measure credit risks of unlisted agricultural enterprises by using the KMV model integrating a CNN-BiLSTM neural network. Initially, the expected default frequencies (EDF) for each listed agricultural enterprise are computed using ...

Mapping spatiotemporal distribution of forest carbon density in Xizang, China.

PloS one
Climate warming is a major global challenge, and forests, essential carbon sinks, are critical in mitigating its effects. Forest carbon density is a key parameter in assessing the carbon sinks. Traditional estimating methods of forest carbon density ...

Temporal trends and machine learning prediction of depressive symptoms among Chinese middle-aged and elderly individuals: a national cohort study.

BMC public health
BACKGROUND: The prevalence of depression symptoms, the third most disabling disease worldwide, is as high as 11.5%-21.1% in China's middle-aged and elderly population and increases significantly with age. It is crucial to identify high-risk groups ef...

Development of a machine learning-based depression risk identification tool for older adults with asthma.

BMC psychiatry
BACKGROUND: Asthma is a chronic inflammatory disorder that adversely affects the quality of life, particularly in older adults. The coexistence of depression in asthma patients complicates their management and exacerbates health outcomes. This study ...

Industrial robot application and total factor productivity of manufacturing enterprises.

PloS one
In the context of intensifying global competitiveness and rapid technological advancement, industrial robots have emerged as a pivotal component in the integration of digital technology, exerting a vital influence on the transformation and enhancemen...

Sentiment analysis of classical Chinese literature: An unsupervised deep learning model with BERT and graph attention networks.

PloS one
Sentiment analysis has become a transformative technology in various contexts, particularly in Natural Language Processing (NLP), social media analytics, and literary analysis, as it can extract information from a wide range of texts. The advancement...

Association between fat-to-muscle ratio and secondary osteoporosis in rheumatoid arthritis: a cross-sectional study at a tertiary hospital in China.

BMJ open
OBJECTIVES: To investigate the correlation between fat-to-muscle ratio (FMR) or other body composition and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA) and to develop a predictive model using FMR and related clinical factors...