Smoking & Tobacco

Designing a Social Snus Cessation Mobile Application with an Integrated AI Function.

The application of artificial intelligence (AI) in healthcare is expected to be increased in the coming years. There has been little attention paid on exploring how social aspects and AI can be integrated into mobile applications to support the people who want to quit snus. Our research aims to design a prototype of a social snus cessation mobile application for university students in Sweden, inco...

Bioimpedance a Diagnostic Tool for Tobacco Induced Oral Lesions: a Mixed Model cross-sectional study

Introduction: Electrical impedance spectroscopy (EIS) has recently developed as a novel diagnostic device for screening and evaluating cervical dysplasia, prostate cancer, breast cancer and basal cell carcinoma. The current study aimed to validate and evaluate bioimpedance as a diagnostic tool for tobacco-induced oral lesions. Methodology: The study comprised 50 OSCC and OPMD tissue specimens fo...

Predicting Cardiovascular Disease Risk in Tobacco Users Using Machine Learning Algorithms.

Cardiovascular Diseases (CVDs) present a substantial global health burden, with tobacco use as a major risk factor. While extensive research has ident...

Can GPT-4 Help Detect Quit Vaping Intentions? An Exploration of Automatic Data Annotation Approach

In recent years, the United States has witnessed a significant surge in the popularity of vaping or e-cigarette use, leading to a notable rise in ca...

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

INTRODUCTION: There has been a rapid proliferation of synthetic nicotine products in recent years, despite newly established regulatory authority and ...

Identifying the Role of Oligodendrocyte Genes in the Diagnosis of Alzheimer's Disease through Machine Learning and Bioinformatics Analysis.

BACKGROUND: Due to the heterogeneity of Alzheimer's disease (AD), the underlying pathogenic mechanisms have not been fully elucidated. Oligodendrocyte...

Artificial Intelligence in Stroke Imaging: A Comprehensive Review.

The aging population challenges the health-care system with chronic diseases. Cerebrovascular diseases are important components of these chronic condi...

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

A comprehensive assessment of cigarette smoking behavior and its effect on health requires a detailed examination of smoke exposure. We propose a CNN-...

Driver identification and fatigue detection algorithm based on deep learning.

In order to avoid traffic accidents caused by driver fatigue, smoking and talking on the phone, it is necessary to design an effective fatigue detecti...

Verification and comparison of three prediction models of ischemic stroke in young adults based on the back propagation neural networks.

This work aims to explore risk factors for ischemic stroke in young adults and analyze the Traditional Vascular Risk Factors Model based on age, hyper...

Support vector machine based classification of smokers and nonsmokers using diffusion tensor imaging.

Despite significant progress in treatments for smoking cessation, smoking continues to be a significant public health concern, especially in young adu...

A Case of Dapsone-induced Mild Methemoglobinemia with Dyspnea and Cyanosis.

Dear Editor, Dapsone is a dual-function drug with antimicrobial and antiprotozoal effects and anti-inflammatory features (1). In dermatology, it is a ...

A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

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 mon...

Innovative Identification of Substance Use Predictors: Machine Learning in a National Sample of Mexican Children.

Machine learning provides a method of identifying factors that discriminate between substance users and non-users potentially improving our ability to...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories about teens whose death from suicide was attributed t...

A Comparison of SVM and CNN-LSTM Based Approach for Detecting Smoke Inhalations from Respiratory signal.

Wearable sensors have successfully been used in recent studies to monitor cigarette smoking events and analyze people's smoking behavior. Respiratory ...

Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive m...

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); however, treatment response to MxS can be heterogeneo...

Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model buildi...

Pulmonary functional parameters and blood cotinine level in chronic obstructive pulmonary disease.

INTRODUCTION: Smoking is the leading cause of chronic obstructive pulmonary disease (COPD) and cotinine is reliable marker of tobacco exposure. We aim...