Smoking & Tobacco

Distinct actin microfilament localization during early cell plate formation through deep learning-based image restoration.

Using deep learning-based image restoration, we achieved high-resolution 4D imaging with minimal photodamage, revealing distinct localization and suggesting Lifeact-RFP-labeled actin microfilaments play a role in initiating cell plate formation. Phragmoplasts are plant-specific intracellular structures composed of microtubules, actin microfilaments (AFs), membranes, and associated proteins. Import...

Rapid Detection of Physicochemical Indicators of Tobacco Flavorings Using Fourier-Transform Near Infrared Spectroscopy with Chemometrics and Machine Learning.

Timely and rapid monitoring of the quality of tobacco flavorings is crucial for the accurate quality management of cigarette products. In this study, FT-NIR spectroscopy combined with chemometrics and machine learning was used to detect physicochemical indicators of tobacco flavorings. FT-NIR spectra of 1,608 flavoring samples, encompassing 145 categories and 90 production batches from actual indu...

SDoH Impact on Periodontal Disease Using Machine Learning and Dental Records.

The impact of social determinants of health (SDoH) on periodontal disease (PD) is critical to study, as a deeper understanding of SDoH offers signific...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (...

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.

There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in pr...

Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.

INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its...

Identification of key therapeutic targets in nicotine-induced intracranial aneurysm through integrated bioinformatics and machine learning approaches.

BACKGROUND: Intracranial aneurysm (IA) is a critical cerebrovascular condition, and nicotine exposure is a known risk factor. This study delves into t...

Testing a Machine Learning-Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial.

BACKGROUND: Individuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interv...

Exploring the ChatGPT platform with scenario-specific prompts for vaping cessation.

OBJECTIVE: To evaluate and start a discussion on the potential usefulness of applying Artificial Intelligence (AI)-driven natural language processing ...

A prediction model based on machine learning: prognosis of HBV-induced HCC male patients with smoking and drinking habits after local ablation treatment.

BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is a major health concern globally and in China, possibly shows recurrence afte...

Machine Learning of Smoking Relapse: the Role of Racial Differences and E-Cigarette Vaping Characteristics on Former Smokers.

BACKGROUND: Machine learning models can help identify multifaceted factors influencing tobacco use transitions. A random forest model is developed to ...

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and increase dementia risk, but their specific magnetic...

Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations.

This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk f...

Establishment and validation of a ResNet-based radiomics model for predicting prognosis in cervical spinal cord injury patients.

Cervical spinal cord injury (cSCI) poses a significant challenge due to the unpredictable nature of recovery, which ranges from mild paralysis to seve...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health. At physiological levels, it acts as an antioxidan...

The association between sports social capital and cognitive health: A longitudinal study of middle-aged and elderly adults in China.

This study examines the association between sports social capital and cognitive health in middle-aged and elderly individuals in China. Using data fro...

Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The major cause of lung disease is tobacco smoke, along wi...

Enhancing cardiovascular risk prediction: the role of wall viscoelasticity in machine learning models.

This study aims to evaluate the significance of wall viscoelasticity in enhancing cardiovascular disease (CVD) risk prediction. We collected data on t...

AI integrations with lung cancer screening: Considerations in developing AI in a public health setting.

Lung cancer screening implementation has led to expanded imaging of the chest in older, tobacco-exposed populations. Growing numbers of screening case...

An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999-2018.

Current research on the association between demographic variables and dietary patterns with atherosclerotic cardiovascular disease (ASCVD) is limited ...