AIMC Topic: Smoking Cessation

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Impact of a Collective Intelligence Tailored Messaging System on Smoking Cessation: The Perspect Randomized Experiment.

Journal of medical Internet research Nov 8, 2016
BACKGROUND: Outside health care, content tailoring is driven algorithmically using machine learning compared to the rule-based approach used in current implementations of computer-tailored health communication (CTHC) systems. A special class of machi...
Humans Machine Learning Female Male Internet Evidence-Based Practice Smoking Cessation Middle Aged Health Communication
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Motivating smokers to quit using computer-generated letters that target either reduction or cessation: A population-based randomized controlled trial among smokers who do not intend to quit.

Drug and alcohol dependence Jul 15, 2016
BACKGROUND: This study examined the long-term efficacy of individualized counseling letters that targeted either smoking abstinence or reducing the number of cigarettes smoked per day to promote future cessation.
Pattern Recognition, Visual Behavior Therapy Counseling Intention Motivation Humans Therapy, Computer-Assisted Female Treatment Outcome Self Care Adult Middle Aged Smoking Cessation Follow-Up Studies Male Models, Theoretical Expert Systems Smoking
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Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications.

International journal of medical informatics Oct 1, 2025
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 re...
Humans Smoking Cessation Artificial Intelligence Tobacco Control Machine Learning Social Media
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A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco Mar 16, 2020
AIMS: Most cigarette smokers want to quit smoking and more than half make an attempt every year, but less than 10% remain abstinent for at least 6 months. Evidence-based tobacco use treatment improves the likelihood of quitting, but more than two-thi...
Machine Learning Female Humans Cotinine Health Behavior Smoking Carbon Monoxide Middle Aged Smoking Cessation Treatment Outcome Cognitive Behavioral Therapy Male
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Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco Jan 4, 2019
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...
Smoking Cessation Ecological Momentary Assessment Smokers Recurrence Tobacco Smoking Smartphone Follow-Up Studies Predictive Value of Tests Proportional Hazards Models Male Middle Aged Adult Humans Machine Learning Female
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