Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
Despite being a major cause of morbidity and mortality, chronic obstructive pulmonary disease (COPD) is frequently undiagnosed. Yet the burden of disease among the undiagnosed is significant, as these individuals experience symptoms, exacerbations, and excess mortality compared to those without COPD. The U.S. Preventive Services Task Force recommends against routine screening of asymptomatic indiv...
Birthweight is often used as a proxy for fetal weight. Problems with this practice have recently been brought to light. We explore whether data available at birth can be used to predict estimated fetal weight using linear and quantile regression, random forests, Bayesian additive regression trees, and generalized boosted models. We train and validate each approach using 18,517 pregnancies (31,948 ...
BACKGROUND: This cross-sectional retrospective study utilized Natural Language Processing (NLP) to extract tobacco-use associated variables from clini...
This study describes a multiphasic approach to the development of a smokeless tobacco cessation program targeted for American Indians (AI) of differen...
Understanding tobacco- and alcohol-related behavioral patterns is critical for uncovering risk factors and potentially designing targeted social compu...
Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can ai...
OBJECTIVE: To characterize vaping behavior and nicotine intake during e-cigarette access.
This study aimed to evaluate the efficiency of Bacillus pumilus AR03 against Altenaria alternata and Erysiphe cichoracearum. The antagonistic activiti...
The aim of the article is to work out the simple approach for matching of the ages of the human and mammalian. The model is based on the analysis of t...
The response of the liver and blood erythrocyte lipids to the low intensity chronic γ-irradiation action of mice at the dose of 8 cGy during early ont...