AIMC Topic: Smoking

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A comparative analysis of heterogeneity in lung cancer screening effectiveness in two randomised controlled trials.

Nature communications
Clinical trials demonstrate that screening can reduce lung cancer mortality by over 20%. However, lung cancer screening effectiveness (reduction in lung cancer specific mortality) may vary by personal risk-factors. Here we evaluate heterogeneity in l...

Lysophospholipid metabolism, clinical characteristics, and artificial intelligence-based quantitative assessments of chest CT in patients with stable COPD and healthy smokers.

Scientific reports
The specific role of lysophospholipids (LysoPLs) in the pathogenesis of chronic obstructive pulmonary disease (COPD) is not yet fully understood. We determined serum LysoPLs in 20 patients with stable COPD and 20 healthy smokers using liquid chromato...

Assessing ChatGPT's suitability in responding to the public's inquires on the effects of smoking on oral health.

BMC oral health
BACKGROUND: With the growing use of Artificial Intelligence (AI) in healthcare, language models like ChatGPT are increasingly being used to provide health information. Given smoking's significant impact on oral health, including periodontal disease, ...

A Robust Cross-Platform Solution With the Sense2Quit System to Enhance Smoking Gesture Recognition: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Smoking is a leading cause of preventable death, and people with HIV have higher smoking rates and are more likely to experience smoking-related health issues. The Sense2Quit study introduces innovative advancements in smoking cessation t...

Predicting children's emotional and behavioral difficulties at age five using pregnancy and newborn risk factors: Evidence from the UK Household Longitudinal Study.

Journal of affective disorders
Childhood emotional and behavioral difficulties have a profound impact on later life outcomes, making it crucial to identify early-life risk factors that predict emotional and behavioral difficulties. However, much of the existing research has concen...

A prediction model based on machine learning: prognosis of HBV-induced HCC male patients with smoking and drinking habits after local ablation treatment.

Frontiers in immunology
BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is a major health concern globally and in China, possibly shows recurrence after ablation treatment in high-risk patients. This study investigates the prognosis of early-stage mal...

Health shocks and health behavior: a long-term perspective.

The European journal of health economics : HEPAC : health economics in prevention and care
Several empirical papers suggest that individuals improve health-related behaviors in response to adverse shocks to physical health. However, little evidence exists regarding the questions of (i) how long-lasting these behavioral responses are and (i...

The Role of Autophagy and Cell Communication in COPD Progression: Insights from Bioinformatics and scRNA-seq.

COPD
Chronic obstructive pulmonary disease (COPD) is characterized by restricted airflow that leads to significant respiratory difficulties. This progressive disease often results in diminished pulmonary function and the onset of additional respiratory co...

Machine learning-enhanced surface-enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta.

Proceedings of the National Academy of Sciences of the United States of America
The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, polycyclic aromatic compounds (PACs), are essential for environmental and health monitoring, for assessing toxicological exposure and their associated ...

Prediction of Aneurysm Sac Shrinkage After Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.

The Journal of surgical research
INTRODUCTION: A simple risk stratification model to predict aneurysm sac shrinkagein patients undergoing endovascular aortic repair (EVAR) for abdominal aortic aneurysms (AAA) was developed using machine learning-based decision tree analysis.