Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
While tobacco advertising innovates at unprecedented speed, traditional surveillance methods remain frozen in time, especially in the context of social media. The lack of large-scale, comprehensive datasets and sophisticated monitoring systems has created a widening gap between industry advancement and public health oversight. This paper addresses this critical challenge by introducing Tobacco-1...
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these domains evolve during a stimulus, with the onset and offset of tones evoking distinct spatial patterns of neural activity. However, it is not known where in the auditory system this spatial segregation occurs or how these dynamics are affected by hear...
Despite promising results in using deep learning to infer genetic features from histological whole-slide images (WSIs), no prior studies have specific...
The upper airway epithelium in humans is maintained in homeostasis by a resident population of basal stem cells. In the presence of tobacco smoke thes...
Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT ...
Despite growing excitement in deploying large language models (LLMs) for healthcare, most machine learning studies show success on the same few limite...
Develop a neighborhood-level framework using machine learning and causal inference to identify socioeconomic and behavioral drivers of Type 2 diabetes...
The propagation of tobacco-related misinformation significantly impacts public health, particularly affecting people with less access to reliable info...
The most effective way to reduce mortality and morbidity among current smokers is to quit smoking. Although about half of smokers attempted to quit, o...
Tobacco use is a critical risk factor for diseases such as cancer and cardiovascular disorders. While electronic health records can capture categorica...
Social and behavioral determinants of health (SBDH) are increasingly recognized as essential for prognostication and informing targeted interventions....
In cardiovascular magnetic resonance (CMR), myocardial native T1 mapping enables quantitative, non-invasive tissue characterization and is sensitive t...
This study aimed to optimise the balance between participant burden and performance of algorithms predicting high-risk moments for a smoking cessation...
Disparities of lung cancer incidence exist in Black populations and screening criteria underserve Black populations due to disparately elevated risk i...
Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can...
To develop privacy-enhancing statistical methods for estimation of binary disease risk model association parameters across multiple electronic health ...
The public health impact of vaping in the United States reflects a complex balance of potential benefits and emerging risks. While e-cigarettes can su...
Should original research routinely contain prominent policy claims, such as recommendations for policymakers or broad calls to action? Growing emphasi...
Oral squamous cell carcinoma (OSCC) remains the most prevalent neoplasm of the head and neck. In recent decades, the incidence and prevalence of OSCC ...
Document classification is considered a critical element in automated document processing systems. In recent years multi-modal approaches have becom...