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 ...

Machine learning approaches for asthma disease prediction among adults in Sri Lanka.

Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine lear...

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.

Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. ...

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-...

FACTORS AFFECTING PROGNOSIS AND MORTALITY IN SEVERE COVID-19 PNEUMONIA PATIENTS.

Fatality rate in coronavirus disease 2019 (COVID-19) cases has been reported to be 3.4% worldwide. The aim of this study was to evaluate the factors t...

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...

A Generic Semi-Supervised and Active Learning Framework for Biomedical Text Classification.

Biomedical text classification requires having training examples labeled by clinical specialists, a process that can be costly. To address this proble...

Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma.

BACKGROUNDPatients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are current...

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 ...

Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes mellitus (DM) type-2, thorough artificial intellig...

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...