AIMC Topic: Cross-Sectional Studies

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Impact of the oxidative balance score on cardiovascular-kidney-metabolic syndrome: A cross-sectional study with machine learning prediction.

PloS one
BACKGROUND AND AIM: The antioxidant diet and lifestyle are widely believed to prevent and even treat various diseases; however, their applicability to cardiovascular-kidney-metabolic (CKM) syndrome remains unknown. In this study, the correlation betw...

Evaluating Large Language Models and Retrieval-Augmented Generation Enhancement for Delivering Guideline-Adherent Nutrition Information for Cardiovascular Disease Prevention: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of death worldwide, yet many web-based sources on cardiovascular (CV) health are inaccessible. Large language models (LLMs) are increasingly used for health-related inquiries and offe...

Machine learning-based identification of small RNA signatures in aqueous humor as a step toward precision diagnosis of glaucoma.

Annals of medicine
BACKGROUND: Glaucoma is a progressive neurodegenerative disease of the optic nerve and one of the leading causes of irreversible blindness worldwide. Small RNAs (including miRNAs) play an important role in the pathogenesis of the disease. Despite ext...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children through prospective and cross-sectional observational studies: a protocol.

BMJ open
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...

Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learning.

BMC surgery
OBJECTIVE: This study aims to develop multiple machine learning models for predicting hypothermia risk in laparoscopic surgery and to perform interpretability analysis of the best-performing model. Our goal is to provide robust decision support for c...

Predicting malnutrition in PLWHIV using machine learning in gondar, Ethiopia.

BMC public health
BACKGROUND: Human Immunodeficiency Virus (HIV) continues to be a major global public health challenge, affecting 39.9 million people globally by the end of 2023. Sub-Saharan Africa bears a significant burden, contributing to 67% of cases. Malnutritio...

Plasma proteome correlations with liver stiffness in pediatric cholestasis implicate epithelial to mesenchymal transition.

Hepatology communications
BACKGROUND: Pediatric cholestatic liver diseases can be characterized by rapidly progressive fibrosis. A multicenter cross-sectional analysis of vibration-controlled elastography in biliary atresia (BA), alpha-1 antitrypsin deficiency (A1AT), and Ala...

Referential hallucination and clinical reliability in large language models: a comparative analysis using regenerative medicine guidelines for chronic pain.

Rheumatology international
This study compared language models' responses to open-ended questions on regenerative therapy guidelines for chronic pain, assessing their accuracy, reliability, usefulness, readability, semantic similarity, and hallucination rates. This cross-secti...