Smoking & Tobacco

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BACKGROUND: Sleep disorders and anxiety-depression symptoms can significantly impair the quality of life and treatment adherence among breast cancer patients undergoing chemotherapy, while also increasing the risk of disease recurrence and mortality. Early identification of the progression trajectory and underlying causes of these symptoms is essential for providing personalized interventions for ...

Morphological parameters contributing to aneurysm rupture: Identifying the rogue from the mugshot using different statistical methods.

INTRODUCTION: Current scores that discriminate rupture status/rupture-associated morphology of aneurysm rupture rely on size being >7 mm, ignoring important morphological parameters. This study applies advanced statistical methods on historical patient data to identify morphological features associated with aneurysms rupture. METHODS: Data from 429 aneurysms along with demographics and morphologic...

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Alcohol use disorder (AUD) research faces significant challenges in capturing individual heterogeneity and complex temporal patterns in drinking behav...

Identifying the ideal deep learning algorithm to quantify the threshold effect of parental smoking on child nutritional status in South Asia.

BACKGROUND: Accurate identification of modifiable risk factors for child malnutrition is of great importance in the formulation of policies to protect...

Tonotopically distinct OFF responses arise in the mouse auditory midbrain following sideband suppression.

The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these d...

An explainable machine learning framework for computable physiologic risk representation in preanesthetic assessment: Development and external validation.

BACKGROUND: Preanesthetic evaluation requires clinicians to synthesize heterogeneous clinical information, yet perioperative risk communication often ...

Association of glycolipid metabolism 6 factors index with cardiovascular and metabolic diseases, and its predictive value in disease progression.

BACKGROUND: The study aims to investigate the potential of glycolipid metabolism 6 factors (GLM6) and glycolipid metabolism 7 factors (GLM7) indexes i...

Scalable nonlinear Cox modeling via random Fourier features with analytic uncertainty.

BACKGROUND: The Cox proportional hazards model often fails to capture complex biomedical risk structures, such as U-shaped biomarker associations, due...

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation.

PURPOSE: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing inter...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...

Integrating ESG indicators and behavioral factors to estimate the mental health index in Italy.

This article examines the relationship between behavioral and Environmental, Social, and Governance (ESG) variables and the Mental Health Index (MHI) ...

A machine learning model for predicting pneumothorax risk after computed tomography-guided percutaneous transthoracic needle biopsy: A two-hospital retrospective study.

Pneumothorax is a common complication after computed tomography-guided percutaneous transthoracic needle biopsy (PTNB), but individualized prediction ...

A machine learning-based framework for predicting hypertension using serum hematological factors.

Hypertension (HTN) is a leading global cause of cardiovascular disease (CVD) and all-cause mortality, underscoring the need for early detection and in...

Association between visceral adiposity index and delayed union/nonunion after tibial or femoral shaft fractures: a single-center retrospective cohort study.

BACKGROUND: Delayed union and nonunion remain clinically important complications after tibial and femoral shaft fractures. Although traditional risk f...

Identification of depression types and key influencing factors among rural elderly in China: a comprehensive analysis based on machine learning and network analysis.

BACKGROUND: Depression poses a severe public health challenge for older adults, especially in rural China. In rural settings, the heavy burden of chro...

Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial.

OBJECTIVES: Computed tomography (CT) scans for lung cancer screening provide the opportunity of quantifying incidental findings. We evaluated the repe...

Prediction of Alzheimer's disease risk factors from retinal images via deep learning: Development and validation of biologically relevant morphological associations in the UK Biobank.

BackgroundThe systemic, metabolic, lifestyle factors have established associations with Alzheimer's disease (AD) through epidemiologic and AD-specific...

Severity-dependent alterations of functional network segregation and integration in tobacco use disorder.

BACKGROUND: Previous research on brain network topology in Tobacco Use Disorder (TUD) has been inconsistent, likely due to overlooking the heterogenei...

Plasma proteomic signatures of cellular aging predict human disease.

Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses...

Factors associated with post-pornography masturbation among university students: a machine-learning study.

BACKGROUND: Pornography consumption is common among university students, yet little research has examined behavioral responses occurring immediately a...