AIMC Topic: Tobacco Products

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YSFER-Tobacco: an effective model for detection of non-tobacco related materials in tobacco sorting process.

Journal of the science of food and agriculture
BACKGROUND: In the process of tobacco sorting, removing non-tobacco related materials (NTRMs) is crucial for the quality of tobacco products. Because of the small size of NTRMs and the abundance and stacking of tobacco leaves, detection of NTRMs is s...

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...

AI for Tobacco Control: Identifying Tobacco-Promoting Social Media Content Using Large Language Models.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
INTRODUCTION: Tobacco companies use social media to bypass marketing restrictions. Studies show that exposure to tobacco promotion on social media influences subsequent smoking behavior, yet it is challenging to monitor such content. We developed an ...

Identification and Characterization of Synthetic Nicotine Product Promotion and Sales on Instagram Using Natural Language Processing.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
INTRODUCTION: There has been a rapid proliferation of synthetic nicotine products in recent years, despite newly established regulatory authority and limited research into its health risks. Previous research has implicated social media platforms as a...

DeepPuff: Utilizing Deep Learning for Smoking Behavior Identification in Free-living Environment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A comprehensive assessment of cigarette smoking behavior and its effect on health requires a detailed examination of smoke exposure. We propose a CNN-LSTM-based deep learning architecture named DeepPuff to quantify Respiratory Smoke Exposure Metrics ...