Hypertension remains a critical global public health challenge, with its complex etiology poorly captured by traditional linear models, especially regarding macro-level structural and gender-specific drivers. To address this, we employed an interpret...
PURPOSE: To evaluate the postoperative pneumonia (POP) risk of patients with non-small cell lung cancer (NSCLC), identify influencing factors, develop a LASSO regression-based model to predict POP risk and identify critical influencing factors.
OBJECTIVE: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis (anti-MDA5 + DM) is a unique subtype of idiopathic inflammatory myopathy (IIM) with a poorer prognosis. The immune-metabolic landscape underlying anti-MDA5 + DM patho...
BACKGROUND: Increasing public acceptance of medical large language models will be beneficial for further leveraging their potential in reducing medical costs and improving efficiency. The objective of our research is to figure out the acceptance of h...
BACKGROUND: In the context of artificial intelligence (AI) profoundly reshaping the educational ecosystem, teachers, as core drivers of the intelligent education era, are facing unprecedented opportunities and mental health challenges. Although AI de...
Chronic diseases are highly prevalent among older adults and may be associated with their ability to achieve successful aging, which encompasses five key components: absence of major chronic diseases, freedom from disability, high cognitive function,...
Despite advancements in modern healthcare, diabetes mellitus remains a lifelong, incurable condition. Empowering patients through health education and self-management is essential in preventing disease progression. This study evaluates the effectiven...
Sports injury prediction is crucial for university football player health, yet existing research predominantly focuses on professional athletes and lacks interpretability. Using the Kaggle "University Football Injury Prediction Dataset" (800 Chinese ...
This study proposes a novel machine learning (ML)-based stacking technique that integrates Single Nucleotide Polymorphisms (SNPs) and inferred local ancestry (LA) to improve predictive accuracy in clinical outcomes. Asthma, particularly severe asthma...
Carbohydrate-protein supplementation often improves endurance performance. However, effectiveness varies significantly among individuals due to unique personal characteristics. This study aimed to develop a predictive machine learning framework for p...
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