Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in early detection and treatment. Furthermore, its epidemiology has undergone a profound transformation, necessitating a radical and comprehensive departure from traditional oncology frameworks. The historical paradigm, which focuses almost exclusively on tobacco smoking as the primary etiological driver, ...
This study explored the use of machine learning (ML) models for cardiovascular risk stratification in an elderly Thai population. A cross-sectional analysis was performed in 210 hypertensive adults aged 60 years and older, using age, sex, systolic blood pressure, smoking status, diabetes mellitus, and body mass index as predictors. Model performance was assessed through 5-fold cross-validation, wi...
Prediabetes (PD), a reversible metabolic condition that precedes type 2 diabetes (T2DM), carries a high risk of progression to T2DM, but can be effect...
Clinical reports contain valuable patient information but are difficult to use due to their unstructured format and privacy constraints. We present MI...
Decades of research aiming to develop effective smoking interventions have identified triggers that contribute to failed quitting attempts including e...
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome represents a primary contributor to global morbidity and mortality. Despite the Life's Esse...
Benzo[a]pyrene (BaP), a polycyclic aromatic hydrocarbon from tobacco smoke, exhaust, and pollutants, is linked to bladder cancer (BLCA). We systematic...
OBJECTIVES: The objective of this research was to examine the content and context-specific information diffusion patterns underlying communication per...
BACKGROUND: To address the aging population in China, local governments began to encourage the establishment of formal care services and supplement in...
BACKGROUND: Tobacco smoking is a leading cause for lung cancer, even for non-smokers. Assessing exposure, particularly to passive or secondhand smoke,...
BACKGROUND: The clinical value of artificial intelligence (AI)-based diagnostic systems depends not only on their accuracy but also on how well their ...
OBJECTIVE: To develop and validate dynamic machine-learning models to predict 6-month adverse outcomes in intermittent claudication (IC), enabling ris...
BACKGROUND: Dyslipidemia is a multifactorial and complex condition that warrants investigation through advanced analytical approaches such as machine ...
BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool to support smoking cessation in primary care, particularly for populations un...
BACKGROUND: Smoking is one of the main preventable causes of premature disease and death. Anti-smoking counseling continues to be a challenge to cover...
BACKGROUND: Hypertension is a major cause of death and disability, and undiagnosed cases are particularly dangerous as they can cause severe damage wi...
PURPOSE: Predictive biomarkers of response to immune checkpoint inhibitors (ICI) remain poorly defined in patients with non-small cell lung cancer (NS...
Staphylococcus aureus causes life-threatening bacterial infections. Current diagnostics for bone infection consist of invasive sample collection and l...
BACKGROUND: Sybil is a deep learning model designed to predict future lung cancer risk based on a single low-dose chest CT (LDCT) scan, facilitating a...
This study aimed to optimise the balance between participant burden and algorithm performance for predicting high-risk moments in a smoking cessation ...