Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
Purpose: Studies based on electronic health records (EHR) often rely on structured data, which may incompletely capture important clinical phenotypes in EHR notes. The purpose of this study was to assess two natural language processing (NLP) tools to extract phenotypes from unstructured EHR notes, and to evaluate the added value of integrating NLP-derived phenotypes with structured EHR data at a h...
BACKGROUND: Tobacco use remains a significant global health challenge, contributing substantially to preventable morbidity and mortality. Despite established interventions, outcomes vary due to scalability issues, resource constraints, and limited reach.
Machine learning methods are increasingly applied to analyze health-related public discourse based on large-scale data, but questions remain regardi...
The use of reinforcement learning (RL) methods to support health behavior change via personalized and just-in-time adaptive interventions is of sign...
Social determinants of health (SDoH) significantly influence health outcomes, shaping disease progression, treatment adherence, and health dispariti...
Comorbidity networks, which capture disease-disease co-occurrence usually based on electronic health records, reveal structured patterns in how dise...
To explore the feasibility of a coronary angiography-based method developed with artificial intelligence which was able to automatically and quickly ...
The problems that tobacco workshops encounter include poor curing, inconsistencies in supplies, irregular scheduling, and a lack of oversight, all o...
INTRODUCTION: Tobacco companies use social media to bypass marketing restrictions. Studies show that exposure to tobacco promotion on social media inf...
Accurately documenting smoking status is essential for clinical decision-making and patient care. However, smoking status information is often only av...
This study investigates changes in resting-state networks (RSNs) associated with tobacco addiction (TA) and whether these changes reflect alterations ...
Forensic genetics has experienced remarkable advancements over the past decades, evolving from the analysis of a limited number of DNA segments to com...
Smoking has been widely identified for its detrimental effects on human health, particularly on the cardiovascular health. The prediction of these eff...
Birth weight (BW) is a key indicator of neonatal health, with low birth weight (LBW) linked to increased mortality and morbidity. Early prediction o...
With the advance of high-throughput genotyping and sequencing technologies, it becomes feasible to comprehensive evaluate the role of massive geneti...
This protocol outlines a scoping review designed to systematically map the existing body of evidence on AI-enabled knowledge sharing in resource-lim...
Addictive behaviour is shaped by the dynamic interaction of implicit, bottom-up and explicit, top-down cognitive processes. In alcohol use disorder (A...
Head and neck squamous cell carcinoma (HNSCC) presents significant challenges in clinical oncology due to its heterogeneity and high mortality rates...
Heart Failure (HF) affects millions of Americans and leads to high readmission rates, posing significant healthcare challenges. While Social Determi...
Importance: Emergency department (ED) returns for mental health conditions pose a major healthcare burden, with 24-27% of patients returning within ...