AIMC Topic: Cigarette Smoking

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Estimating substance use disparities across intersectional social positions using machine learning: An application of group-lasso interaction network.

Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors
OBJECTIVE: An aim of quantitative intersectional research is to model the joint impact of multiple social positions on health risk behaviors. Although moderated multiple regression is frequently used to pursue intersectional research hypotheses, such...

Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.

Substance use & misuse
Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A previous clinical trial suggests that Goal2Quit, a behavioral activation-based smoking cessation mobile app, effectively increases smoking abstinence an...

Mechanism of cytotoxicity induced by the cigarette smoke extract (CSE) of heated tobacco products in vascular smooth muscle cells: A comparative study of the cytotoxic effects of CSE and the ferroptosis inducer, erastin.

Journal of pharmacological sciences
Heated tobacco products (HTPs) are marketed worldwide as less harmful alternatives to combustible cigarettes; however, their cytotoxic mechanisms in vascular smooth muscle cells are poorly understood. Ferroptosis is defined as iron-dependent cell dea...

Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach.

BMC pulmonary medicine
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases. The diagnosis of COPD is generally based on the pulmonary function testing, however, difficulties underlie in prognosis of smokers or early stage of...

Assessing data availability and quality within an electronic health record system through external validation against an external clinical data source.

BMC medical informatics and decision making
BACKGROUND: Approximately 20% of deaths in the US each year are attributable to smoking, yet current practices in the recording of this health risk in electronic health records (EHRs) have not led to discernable changes in health outcomes. Several gr...

Natural Language Processing for Asthma Ascertainment in Different Practice Settings.

The journal of allergy and clinical immunology. In practice
BACKGROUND: We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic.

Screening of oxidative stress components of cigarette smoke based on machine learning model integration.

Toxicology and applied pharmacology
Cigarette smoke, a complex mixture of more than 7000 chemicals, poses a significant threat to human health, with oxidative stress being an important mechanism in its associated diseases. Traditional methods for assessing the toxicity of cigarette smo...